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Free Download YOLOv12 - Custom Object Detection, Tracking & Webapps Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 8.35 GB | Duration: 5h 0m YOLOv12, Learn Custom Object Detection and Tracking with YOLOv12, and Build Web Apps with Flask What you'll learn YOLOv12 architecture and how it really works What is Non Maximum Suppression & Mean Average Precision How to use YOLOv12 for Object Detection Evaluating YOLOv12 Model Performance on Images, Videos & on the Live Webcam Feed Blurring Objects with YOLOv12 and OpenCV-Python Data annotation/labeling using Roboflow Build a Tennis Analysis System with YOLO, OpenCV and PyTorch Training and Fine-Tuning YOLOv12 Models on Custom Datasets Object Detection in the Browser using YOLOv12 and Flask Requirements Mac / Windows / Linux - all operating systems work with this course! Description YOLOv12 is the latest state-of-the-art computer vision model architecture, surpassing previous versions in both speed and accuracy. Built upon the advancements of earlier YOLO models, YOLOv12 introduces significant architectural and training enhancements, making it a versatile tool for various computer vision tasks.The YOLOv12 model supports a wide range of tasks, including object detection, instance segmentation, image classification, pose estimation, and oriented object detection (OBB).Course StructureThis course is divided into multiple sections, covering everything from the fundamentals of YOLOv12 to advanced applications.Introduction to YOLOv12What's New in YOLOv12Key updates and features in YOLOv12Non-Maximum Suppression & Mean Average Precision in Computer VisionRunning YOLOv12Setting up YOLOv12Using YOLOv12 for Object DetectionEvaluating YOLOv12 Model Performance: Testing and AnalysisDataset PreparationHow to find and prepare datasetsData annotation, labeling, and automatic dataset splittingTraining YOLOv12Fine-Tuning YOLOv12 for Object Detection on Custom DatasetsCustom Projects:Train YOLOv12 for Personal Protective Equipment (PPE) DetectionTrain YOLOv12 for Potholes DetectionAdvanced Multi-Object TrackingImplementing Multi-Object tracking with Bot-SORT and ByteTrack algorithmsAdvanced ApplicationsBlurring Objects with YOLOv12 and OpenCV-PythonGenerating Intensity Heatmaps to Identify Congestion ZonesBuilding a Tennis Analysis System with YOLO, OpenCV, and PyTorchWeb IntegrationDeveloping Web Apps with YOLOv12 and Flask Anyone who is interested in Computer Vision,Anyone who study Computer Vision and want to know how to use YOLOv12 for Object Detection,Anyone who aims to build Deep learning Apps with Computer Vision Homepage: https://www.udemy.com/course/yolov12-custom-object-detection-tracking-webapps/ Rapidgator https://rg.to/file/05f82a6de158c11c0fbda0302294b34f/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part01.rar.html https://rg.to/file/5456a43bf6abc8a9ef5a58a5633402c8/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part02.rar.html https://rg.to/file/85198f3f8ae8743f35ff58f48e4fc023/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part03.rar.html https://rg.to/file/e05387d0358232614e00e1ee9419eb04/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part04.rar.html https://rg.to/file/471a71443cce9581fe18b97ea3e51fd3/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part05.rar.html https://rg.to/file/3ac7f47d7fd8ce266c17b76bef1603d9/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part06.rar.html https://rg.to/file/96ab8d3c26797b507de453e934053afc/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part07.rar.html https://rg.to/file/38fb31ce126a54f155fb85ae99043c7f/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part08.rar.html https://rg.to/file/46e2123cf871c16df1be5bcc6a21c630/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part09.rar.html Fikper Free Download https://fikper.com/fod4YmS42e/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part01.rar.html https://fikper.com/5z7DgOznJw/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part02.rar.html https://fikper.com/3yCHytTBY2/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part03.rar.html https://fikper.com/XqNkVBQBz9/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part04.rar.html https://fikper.com/dhUyxHC05f/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part05.rar.html https://fikper.com/DUtFJL8mU3/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part06.rar.html https://fikper.com/B0eOC8Ku72/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part07.rar.html https://fikper.com/B6Z0rvuwwp/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part08.rar.html https://fikper.com/ULBgLQP3Zd/mffew.YOLOv12.Custom.Object.Detection.Tracking..Webapps.part09.rar.html No Password - Links are Interchangeable

Free Download Flutter Pose Detection - Build AI-Powered Fitness & Yoga Apps Published: 3/2025 Created by: Mobile ML Academy by Hamza Asif MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 48 Lectures ( 3h 58m ) | Size: 2.47 GB Learn Pose Detection in Flutter to Build AI-Powered Fitness & Yoga Apps with Real-Time Motion Tracking & Exercise Count What you'll learn Integrate pose detection models in Flutter to track human body movements Detect yoga poses and exercises using AI-powered pose estimation Process images and live camera footage for real-time motion tracking Build a yoga trainer app that evaluates and recognizes different poses Develop an AI-powered exercise counter that tracks and counts workouts Use Flutter & Dart to create intelligent fitness and wellness applications Understand key points and joints detection for body movement analysis Apply pose detection in various domains, including fitness, sports, and healthcare Gain hands-on experience with practical, real-world Flutter projects Requirements Basic understanding of mobile app development concepts is helpful but not mandatory A physical or virtual Android/iOS device for testing real-time pose detection Description Do you want to build intelligent mobile apps that can understand human movements, detect yoga poses, and count exercises in real-time? If so, this course is for you!In this comprehensive course, you'll learn how to integrate pose detection models into Flutter apps from scratch. Whether you're building fitness trackers, AI-powered yoga trainers, or interactive gaming applications, pose detection allows you to analyze human body movements by identifying key points-such as shoulders, elbows, knees, and ankles.What You'll Learn in This CourseIntroduction to Pose Detection and its real-world applications in fitness, sports, healthcare, and gamingHow to integrate pose detection models in Flutter using both images and live camera footageDevelop AI-powered apps, including:A Yoga Trainer App that detects and evaluates yoga posesAn Exercise Counter App that tracks body movements and counts repetitions in real-timeProcess pose detection results to recognize body postures and improve user experienceReal-time pose detection in Flutter for interactive applicationsBuild ML-based fitness tracking apps in Flutter from scratchCourse StructureIntroduction to Pose Detection - Understanding key points, joints, and motion trackingPose Detection with Images - Select images from the gallery or capture with the camera, process poses, and detect exercisesReal-time Pose Detection - Implement AI-powered motion tracking to detect and count workouts instantlyHands-on Flutter Projects - Step-by-step guidance on building interactive, ML-based fitness and wellness appsWho Is This Course For?Flutter developers (beginners & experienced) who want to integrate AI-based pose detectionMobile app developers looking to enhance apps with real-time motion trackingFitness & wellness app creators who want to build interactive workout applicationsAnyone interested in Flutter app development and AI-powered mobile experiencesWhy Take This Course?Hands-on projects for real-world experienceStep-by-step guidance to integrate pose detection in FlutterNo prior machine learning knowledge required - just basic Flutter & DartJoin us today and start building the next generation of AI-powered fitness, wellness, and gaming apps in Flutter. Let's get moving! Who this course is for Students & professionals eager to learn Flutter app development with practical AI applications Flutter developers (beginners & experienced) who want to integrate AI-based pose detection into their apps Anyone who want to build AI-powered exercise and yoga apps Mobile app developers looking to enhance apps with real-time motion tracking Homepage: https://www.udemy.com/course/flutter-pose-detection-build-ai-powered-fitness-yoga-apps/ Rapidgator https://rg.to/file/27606ff6560d6754ef8216a66d7b60b0/fdflw.Flutter.Pose.Detection.Build.AIPowered.Fitness..Yoga.Apps.part1.rar.html https://rg.to/file/90f169b03193007e5e84a4e34bc016f6/fdflw.Flutter.Pose.Detection.Build.AIPowered.Fitness..Yoga.Apps.part2.rar.html https://rg.to/file/608a84528a4ef44ed38b52267ecd08a6/fdflw.Flutter.Pose.Detection.Build.AIPowered.Fitness..Yoga.Apps.part3.rar.html Fikper Free Download https://fikper.com/6c1ZG8C4aa/fdflw.Flutter.Pose.Detection.Build.AIPowered.Fitness..Yoga.Apps.part1.rar.html https://fikper.com/cHXHtgiXh2/fdflw.Flutter.Pose.Detection.Build.AIPowered.Fitness..Yoga.Apps.part2.rar.html https://fikper.com/MrvYYhw79g/fdflw.Flutter.Pose.Detection.Build.AIPowered.Fitness..Yoga.Apps.part3.rar.html No Password - Links are Interchangeable

Free Download Outlier Detection in Python, Video Edition By Brett Kennedy Released 12/2024 By Brett Kennedy MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 19h 35m | Size: 3.37 GB Learn how to identify the unusual, interesting, extreme, or inaccurate parts of your data. Data scientists have two main tasks: finding patterns in data and finding the exceptions. These outliers are often the most informative parts of data, revealing hidden insights, novel patterns, and potential problems. Outlier Detection in Python is a practical guide to spotting the parts of a dataset that deviate from the norm, even when they're hidden or intertwined among the expected data points. In Outlier Detection in Python you'll learn how to Use standard Python libraries to identify outliers Select the most appropriate detection methods Combine multiple outlier detection methods for improved results Interpret your results effectively Work with numeric, categorical, time series, and text data Outlier detection is a vital tool for modern business, whether it's discovering new products, expanding markets, or flagging fraud and other suspicious activities. This guide presents the core tools for outlier detection, as well as techniques utilizing the Python data stack familiar to data scientists. To get started, you'll only need a basic understanding of statistics and the Python data ecosystem. About the Technology Outliers-values that appear inconsistent with the rest of your data-can be the key to identifying fraud, performing a security audit, spotting bot activity, or just assessing the quality of a dataset. This unique guide introduces the outlier detection tools, techniques, and algorithms you'll need to find, understand, and respond to the anomalies in your data. About the Book Outlier Detection in Python illustrates the principles and practices of outlier detection with diverse real-world examples including social media, finance, network logs, and other important domains. You'll explore a comprehensive set of statistical methods and machine learning approaches to identify and interpret the unexpected values in tabular, text, time series, and image data. Along the way, you'll explore scikit-learn and PyOD, apply key OD algorithms, and add some high value techniques for real world OD scenarios to your toolkit. What's Inside Python libraries to identify outliers Combine outlier detection methods Interpret your results About the Reader For Python programmers familiar with tools like pandas and NumPy, and the basics of statistics. https://www.oreilly.com/library/view/outlier-detection-in/9781633436473VE https://fileaxa.com/36r8xi3rwe4f https://fileaxa.com/9tadmfbka53g https://fileaxa.com/lc3jbz4o5opz https://fileaxa.com/uon9kj799n2o https://takefile.link/w8186dqt0oh4/sxxzh.Outlier.Detection.in.Python.Video.Edition.part1.rar.html https://takefile.link/ix24bdysqyr3/sxxzh.Outlier.Detection.in.Python.Video.Edition.part2.rar.html https://takefile.link/m3uedbq1yo4r/sxxzh.Outlier.Detection.in.Python.Video.Edition.part3.rar.html https://takefile.link/9exxgrn5zqjf/sxxzh.Outlier.Detection.in.Python.Video.Edition.part4.rar.html Rapidgator https://rg.to/file/305d1ce7eaaf0c3b13b50f356f3f0f02/sxxzh.Outlier.Detection.in.Python.Video.Edition.part1.rar.html https://rg.to/file/af1b98c392164dd0b95ab8cdd06ab629/sxxzh.Outlier.Detection.in.Python.Video.Edition.part2.rar.html https://rg.to/file/63640662cae1c67050e734ff2c88f923/sxxzh.Outlier.Detection.in.Python.Video.Edition.part3.rar.html https://rg.to/file/b2871ad4c2b3cb059f6f817ea7249328/sxxzh.Outlier.Detection.in.Python.Video.Edition.part4.rar.html Fikper Free Download https://fikper.com/GX0BqWKU8o/sxxzh.Outlier.Detection.in.Python.Video.Edition.part1.rar.html https://fikper.com/QdSv90S6oW/sxxzh.Outlier.Detection.in.Python.Video.Edition.part2.rar.html https://fikper.com/pfABHEVsvv/sxxzh.Outlier.Detection.in.Python.Video.Edition.part3.rar.html https://fikper.com/VeL7an2LFm/sxxzh.Outlier.Detection.in.Python.Video.Edition.part4.rar.html No Password - Links are Interchangeable

Free Download AI For Fraud Detection And Suspicious Transaction Monitoring Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.25 GB | Duration: 4h 55m AI in Banking Security - 10 Banks and 8 technology AI solutions covered. What you'll learn Understand the importance of transaction monitoring and suspicious activity detection in banking. Explore how AI enhances transaction monitoring systems in financial institutions. Risk Indicators, Regulations, and Compliance Understand the role of Know Your Customer (KYC) and Anti-Money Laundering (AML) regulations in transaction monitoring. AI and Machine Learning in Fraud Detection Get hands-on insights into the implementation of a neural network fraud detection model. Transaction Types and AI Solutions Study successful AI use cases from HSBC, JPMorgan Chase, Standard Chartered Bank, Danske Bank, ING Bank, DBS Bank, ICICI Bank, China Construction Bank (CCB) etc Requirements Basic Finance & Banking Knowledge Description The financial industry faces an ever-growing challenge in detecting and preventing fraudulent transactions and money laundering activities. With the rapid advancements in artificial intelligence (AI), banks and financial institutions are now leveraging AI-driven solutions to enhance transaction monitoring, detect suspicious activities, and comply with regulatory frameworks. This course, AI for Fraud Detection and Suspicious Transaction Monitoring in Banking, is designed to provide a comprehensive understanding of AI applications in financial fraud detection, covering key concepts, methodologies, and real-world case studies from leading global banks.The course begins with an Introduction, providing an Overview of fraud detection and the Importance of Transaction Monitoring & Suspicious Activity in banking. It explores the Challenges in Traditional Suspicious Activity Detection, highlighting the limitations of conventional fraud detection systems and the need for AI-driven solutions. Learners will gain insights into How AI Enhances Transaction Monitoring Systems, improving accuracy and reducing false positives.A key focus of this course is on Key Risk Indicators (KRIs) and Red Flags in Transactions, which help financial institutions identify potential fraudulent activities. The course further delves into the Role of Know Your Customer (KYC) and Anti-Money Laundering (AML) Regulations, with a detailed examination of Regulatory Frameworks such as FATF, FinCEN, and GDPR. Learners will explore AI-Driven KYC and AML Solutions in Financial Institutions, studying successful implementations in the industry.The course also covers Key NLP Techniques in Financial Transaction Monitoring, Anomaly Detection Algorithms (Supervised vs. Unsupervised Learning), and Neural Networks and AI Models for Fraud Detection. Practical implementation is emphasized through an Implementation Guide for Deploying a Neural Network Fraud Detection Model and Data Collection & Preprocessing for AI Models.A specialized section on Types of Transactions in Banks and the Role of AI explains why trade transactions are closely monitored and how AI enhances surveillance. It examines the High Volume of Transactions & AI Solutions, The Complexity of Financial Instruments & AI Solutions, and how AI helps in Detecting Emerging Financial Crimes.The course also addresses Regulatory Complexity & AI Solutions, Adaptability to Existing Legacy Systems, and Security & Data Privacy Issues. With rapidly developing AI technologies, banks face challenges in implementation, and the course discusses Resource Restrictions & AI Solutions to navigate these issues.The course features in-depth Real-World Case Studies, showcasing AI-driven fraud detection solutions in leading global banks, including HSBC, JPMorgan Chase, Standard Chartered Bank, Danske Bank, ING Bank, DBS Bank, ICICI Bank, China Construction Bank (CCB), Mitsubishi UFJ Financial Group (MUFG), and Hang Seng Bank. These case studies highlight how these financial institutions successfully deploy AI in combating financial fraud, money laundering, and trade-based money laundering (TBML).By the end of the course, learners will gain a strong understanding of AI's role in fraud detection and transaction monitoring, equipping them with the knowledge to implement AI-driven solutions in banking and finance. The course is ideal for banking professionals, compliance officers, data scientists, and AI enthusiasts looking to enhance their expertise in AI-powered fraud detection. 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Free Download YOLO11 - Custom Object Detection & Web Apps in Python 2024 Published 10/2024 Created by Muhammad Moin MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 10 Lectures ( 5h 28m ) | Size: 5.55 GB Learn Custom Object Detection, Tracking and Pose Estimation with YOLO11, and Build Web Apps with Flask and Streamlit What you'll learn Object Detection, Instance Segmentation, Pose Estimation and Image Classification using YOLO11 Training / Fine-Tuning YOLO11 Models on Custom Dataset Multi-Object Tracking with Ultralytics YOLO Develop Streamlit Application for Object Detection with YOLO11. Object Detection in the Browser using YOLO11 and Flask Requirements Mac / Windows / Linux - all operating systems work with this course! Description YOLO11 is the latest state-of-the-art object detection model from Ultralytics, surpassing previous versions in both speed and accuracy. Built upon the advancements of earlier YOLO models, YOLO11 introduces significant improvements in architecture and training, making it a versatile tool for various computer vision tasks.YOLO11 models support a wide range of tasks, including object detection, instance segmentation, image classification, pose estimation, and oriented object detection (OBB).In this course, you will learn:What's New in Ultralytics YOLO11.How to use Ultralytics YOLO11 for Object Detection, Instance Segmentation, Pose Estimation, and Image Classification.Running Object Detection, Instance Segmentation Pose Estimation and Image Classification with YOLO11 on Windows/Linux.Evaluating YOLO11 Model Performance: Testing and AnalysisTraining a YOLO11 Object Detection Model on a Custom Dataset in Google Colab for Personal Protective Equipment (PPE) Detection. Step-by-Step Guide: YOLO11 Object Detection on Custom Datasets on Windows/Linux.Training YOLO11 Instance Segmentation on Custom Datasets for Pothole Detection.Fine-Tuning YOLO11 Pose Estimation for Human Activity Recognition.Fine-Tuning YOLO11 Image Classification for Plant Classification.Multi-Object Tracking with Bot-SORT and ByteTrack Algorithms.License Plate Detection & Recognition using YOLO11 and EasyOCR.Integrating YOLO11 with Flask to Build a Web App.Creating a Streamlit Web App for Object Detection with YOLO11. Who this course is for Anyone who is interested in Computer Vision Anyone who study Computer Vision and want to know how to use YOLO11 for Object Detection, Instance Segmentation, Pose Estimation and Image Classification Anyone who aims to build Deep learning Apps with Computer Vision Homepage https://www.udemy.com/course/yolo11-custom-object-detection-web-apps-in-python-2024/ Screenshot Rapidgator https://rg.to/file/3348e9834520199e318fc6646ee4b69e/pgzwh.YOLO11.Custom.Object.Detection..Web.Apps.in.Python.2024.part6.rar.html https://rg.to/file/5878e6ffbfdf62eadb092d0ff9bba3fc/pgzwh.YOLO11.Custom.Object.Detection..Web.Apps.in.Python.2024.part4.rar.html https://rg.to/file/a1d78d8f677fe96aa0bb0b56f0be25d0/pgzwh.YOLO11.Custom.Object.Detection..Web.Apps.in.Python.2024.part1.rar.html https://rg.to/file/a5050dfb6786f094187ce6ce4f9edf39/pgzwh.YOLO11.Custom.Object.Detection..Web.Apps.in.Python.2024.part2.rar.html https://rg.to/file/d661f23261a71a913c134663fce8e4ee/pgzwh.YOLO11.Custom.Object.Detection..Web.Apps.in.Python.2024.part5.rar.html https://rg.to/file/e312cef65aacba78ca3eb9d9a07c9af4/pgzwh.YOLO11.Custom.Object.Detection..Web.Apps.in.Python.2024.part3.rar.html Fikper Free Download https://fikper.com/H2vX0bkj6C/pgzwh.YOLO11.Custom.Object.Detection..Web.Apps.in.Python.2024.part2.rar.html https://fikper.com/TcAj6lNgFR/pgzwh.YOLO11.Custom.Object.Detection..Web.Apps.in.Python.2024.part3.rar.html https://fikper.com/WOeP4ThHnV/pgzwh.YOLO11.Custom.Object.Detection..Web.Apps.in.Python.2024.part4.rar.html https://fikper.com/jgIhlSSdul/pgzwh.YOLO11.Custom.Object.Detection..Web.Apps.in.Python.2024.part1.rar.html https://fikper.com/uoFCWt9La2/pgzwh.YOLO11.Custom.Object.Detection..Web.Apps.in.Python.2024.part6.rar.html https://fikper.com/xFBQanVE8q/pgzwh.YOLO11.Custom.Object.Detection..Web.Apps.in.Python.2024.part5.rar.html No Password - Links are Interchangeable

Free Download Fire Detection & Alarm System Published 10/2024 Created by Vikas Sinwar MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 16 Lectures ( 2h 43m ) | Size: 2.6 GB An Overview of Fire Detection, Fire Alarm, Fire sprinkler and Fire suppression System What you'll learn What is fire alarm and detection system Different Types of Fire Alarm Systems Different type of detectors and devices used in fire detection/alarm system Design and installation of devices Requirements No prior fire alarm and detection experience needed. This Course will guide those new to the industry or professional for those who need a different explanation of topics Description Hello Students !Welcome to this course on, "The Fire Detection & Alarm System".Goal of this course is to understand the requirement of fire detection system. We will understand different types of fire alarm system and which one to use depending upon site conditions. Detail knowledge about all devices used in fire detection and alarm system. Guidelines to keep in mind while Design and Installation fire detection system. New technologies like wireless fire alarm system is also added. Fire sprinkler and fire suppression system will be also discussed.This course covers the in-depth knowledge of following topics:1. Fire detection system2. Smoke detector3. Het detector4. Beam detector5. Multi detector6. Response Indicator7. Hooter8. Manual call point9. Repeater panel10. Main fire panel11. Fault Isolator12. Conventional fire alarm system13. Addressable fire alarm system14. Different type of wiring15. Design and detector spacing requirement16. Maintenance and testing of fire alarm system17. Wireless fire alarm system18. Fire sprinkler and fire suppression systemBy the end of the course, you will have a comprehensive understanding of fire detection system, different devices used, different type of fire detection system, design, installation and testing of devices, wireless fire alarm system, fire sprinkler and fire suppression system.Enroll in the "Fire Detection & Alarm System "course and advance your career in fire safety. Who this course is for Fresher in fire detection and alarm sector Fire protection engineers Fire safety manager Technician in fire safety industry Anyone who need to design their own home detection Consultant, building design experts Students Homepage https://www.udemy.com/course/fire-detection-alarm-system/ Screenshot Rapidgator https://rg.to/file/23d0ffdaec34c96e8f6224fb6f52d9fa/xyzsw.Fire.Detection..Alarm.System.part3.rar.html https://rg.to/file/57f63424b40900d9a0ca3042193331dc/xyzsw.Fire.Detection..Alarm.System.part2.rar.html https://rg.to/file/882c52c65cdf604e48fa2edbf51795ee/xyzsw.Fire.Detection..Alarm.System.part1.rar.html Fikper Free Download https://fikper.com/85fLk2FugO/xyzsw.Fire.Detection..Alarm.System.part1.rar.html https://fikper.com/LHLk8Gyd5F/xyzsw.Fire.Detection..Alarm.System.part3.rar.html https://fikper.com/bEfsn6mTFM/xyzsw.Fire.Detection..Alarm.System.part2.rar.html No Password - Links are Interchangeable

Free Download Applied Computer Vision Object Detection and Recognition Published 10/2024 Created by Vahid Mirjalili, PhD,Taban Eslami MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 44 Lectures ( 2h 14m ) | Size: 853 MB Object Recognition From Basics to Advanced Techniques What you'll learnUnderstand the fundamentals of image recognition, including image classification, object detection, and image segmentation (semantic, instance, and panoptic)) Master the underlying theories and principles of key computer vision models, enabling a deep understanding of their functionality and applications Master PyTorch fundamentals, learn how to build a CNN model, and your custom image dataset Implement advanced image recognition models and train them in PyTorch RequirementsPython Programming Experience: Familiarity with programming, particularly in Python, as it's the primary language used with PyTorch. Students should be comfortable with basic programming concepts and structures. Understanding of Basic Machine Learning Concepts: A foundational knowledge of machine learning principles, including what models are, how they are trained, and a basic understanding of concepts like classification, regression, overfitting, and underfitting. Introductory Knowledge of Deep Learning: Familiarity with the basic concepts of neural networks, including what they are and how they are generally structured and trained. DescriptionComputer Vision and Object RecognitionThis course provides a comprehensive journey into computer vision and object recognition, guiding you from the foundational concepts to advanced model implementation and evaluation. Through a hands-on approach, you will explore key computer vision tasks such as image classification, object detection, semantic segmentation, and instance segmentation. The course uses popular datasets like COCO-2017 and CamVid, and frameworks such as PyTorch and FiftyOne to enhance your practical skills.Section 1: Introduction We begin with an overview of the course and object recognition, followed by setting up the necessary environment for efficient implementation.Section 2: Recap of Convolutional Neural Networks (CNNs) This section refreshes your knowledge of CNNs and introduces essential tools like FiftyOne for dataset management, along with tutorials to get familiar with PyTorch.Section 3: Image Classification You will learn to build and train a multi-class image classifier using the COCO-2017 dataset, focusing on classes like cats, dogs, and horses. The classifier is built using a pre-trained ResNet model, demonstrating the process of transfer learning and hyperparameter tuning.Section 4: Object Detection We delve into object detection using two popular models, Faster-RCNN and YOLOv8. You'll prepare datasets, train both models, and analyze their performance using FiftyOne, gaining hands-on experience with both region-based and single-shot detection methods.Section 5: Semantic Segmentation In this section, you will work with the CamVid dataset to understand semantic segmentation, which involves assigning a class to every pixel in an image. Using the segmentation_models_pytorchlibrary, you will train and evaluate a segmentation model to recognize objects in scenes.Section 6: Instance Segmentation We cover instance segmentation, where the goal is to differentiate between multiple instances of the same object class. You'll build and train a Mask-RCNN model for this task, working with segmentation annotations from the COCO-2017 dataset.Throughout the course, we place a strong emphasis on hands-on exercises, real-world datasets, and model evaluation to equip you with the skills needed to tackle practical computer vision challenges. By the end, you will be well-prepared to implement and evaluate various computer vision models, with a solid understanding of the nuances involved in different tasks like classification, detection, and segmentation. Who this course is forStudents and Learners in Computer Science: Undergraduate or graduate students who are majoring in computer science, data science, artificial intelligence, or related fields and want to gain practical skills in image recognition using PyTorch. Aspiring Data Scientists and Machine Learning Engineers: Individuals looking to enter the field of data science or machine learning with a specific interest in image processing and recognition techniques. AI and Machine Learning Enthusiasts: Individuals who have a keen interest in artificial intelligence and machine learning and want to deepen their understanding of image recognition. Tech Entrepreneurs: Entrepreneurs or innovators looking to understand image recognition to implement or improve product offerings, particularly in tech-driven markets. Homepage https://www.udemy.com/course/applied-computer-vision/ Rapidgator https://rg.to/file/46055b26242e55dd14d3d3bebc61a186/cqinv.Applied.Computer.Vision.Object.Detection.and.Recognition.rar.html Fikper Free Download https://fikper.com/6THTR8RTbL/cqinv.Applied.Computer.Vision.Object.Detection.and.Recognition.rar.html No Password - Links are Interchangeable

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Lynda - Windows Performance Toolkit: Spyware Detection Size: 726 MB | Duration: 0h 55m | Video: AVC (.mp4) 1280x720 15&30fps | Audio: AAC 48KHz 2ch Genre: eLearning | Level: Intermediate | Language: English Is your PC running slow? The answer might be more nefarious than you think. Is your PC running slow? The answer might be more nefarious than you think. Spyware such as keyloggers can often go undetected by antivirus software. Windows Performance Toolkit offers two powerful tools for identifying and gathering evidence of keyloggers: the Recorder, used to record system events, and the Analyzer, used to inspect those events. Join Thomas Pantels as he explains what a keylogger is and demonstrates how it functions and hides in plain sight. Using Windows Performance Toolkit, he shows how to set up a profiling environment to gather evidence and find the keylogger "hooks. " Once you've traced the keylogger, you can delete the application and get your computer back on track. Download link: http://rapidgator.net/file/028532f058c05762a9ea04b9d3b97916/xgq1f.Lynda..Windows.Performance.Toolkit.Spyware.Detection.rar.html]xgq1f.Lynda..Windows.Performance.Toolkit.Spyware.Detection.rar.html http://nitroflare.com/view/068929EF28BEC2E/xgq1f.Lynda..Windows.Performance.Toolkit.Spyware.Detection.rar]xgq1f.Lynda..Windows.Performance.Toolkit.Spyware.Detection.rar http://uploaded.net/file/rkavsjfq/xgq1f.Lynda..Windows.Performance.Toolkit.Spyware.Detection.rar]xgq1f.Lynda..Windows.Performance.Toolkit.Spyware.Detection.rar https://www.bigfile.to/file/Sgwx6VBPexa3/xgq1f.Lynda..Windows.Performance.Toolkit.Spyware.Detection.rar]xgq1f.Lynda..Windows.Performance.Toolkit.Spyware.Detection.rar Links are Interchangeable - No Password - Single Extraction

Lynda - Windows Performance Toolkit: Spyware Detection Size: 726 MB | Duration: 0h 55m | Video: AVC (.mp4) 1280x720 15&30fps | Audio: AAC 48KHz 2ch Genre: eLearning | Level: Intermediate | Language: English Is your PC running slow? The answer might be more nefarious than you think. Is your PC running slow? The answer might be more nefarious than you think. Spyware such as keyloggers can often go undetected by antivirus software. Windows Performance Toolkit offers two powerful tools for identifying and gathering evidence of keyloggers: the Recorder, used to record system events, and the Analyzer, used to inspect those events. Join Thomas Pantels as he explains what a keylogger is and demonstrates how it functions and hides in plain sight. Using Windows Performance Toolkit, he shows how to set up a profiling environment to gather evidence and find the keylogger "hooks. " Once you've traced the keylogger, you can delete the application and get your computer back on track. DOWNLOAD http://rapidgator.net/file/70e302d9f1ac1a5524f14d8650b79b45/lt8ri.Lynda..Windows.Performance.Toolkit.Spyware.Detection.rar.html https://bytewhale.com/z2q1o5z5p4ef/lt8ri.Lynda..Windows.Performance.Toolkit.Spyware.Detection.rar http://uploaded.net/file/akj7k7tx/lt8ri.Lynda..Windows.Performance.Toolkit.Spyware.Detection.rar https://www.bigfile.to/file/kE4zj3DDqs7X/lt8ri.Lynda..Windows.Performance.Toolkit.Spyware.Detection.rar http://nitroflare.com/view/C8C06AD0D20D6AC/lt8ri.Lynda..Windows.Performance.Toolkit.Spyware.Detection.rar http://uploadgig.com/file/download/991fD12b332bCcc6/lt8ri.Lynda..Windows.Performance.Toolkit.Spyware.Detection.rar

Lynda - Windows Performance Toolkit: Spyware Detection Duration: 0h 55m | Video: AVC (.mp4) 1280x720 15&30fps | Audio: AAC 48KHz 2ch | 726 MB Genre: eLearning | Level: Intermediate | Language: English Is your PC running slow? The answer might be more nefarious than you think. Spyware such as keyloggers can often go undetected by antivirus software. Windows Performance Toolkit offers two powerful tools for identifying and gathering evidence of keyloggers: the Recorder, used to record system events, and the Analyzer, used to inspect those events. Join Thomas Pantels as he explains what a keylogger is and demonstrates how it functions and hides in plain sight. Using Windows Performance Toolkit, he shows how to set up a profiling environment to gather evidence and find the keylogger "hooks. " Once you've traced the keylogger, you can delete the application and get your computer back on track. Download link: http://rapidgator.net/file/cc55fcf617e2d8cc03d3210112ddcbb3/z5ewu.Windows.Performance.Toolkit.Spyware.Detection.part1.rar.html]z5ewu.Windows.Performance.Toolkit.Spyware.Detection.part1.rar.html http://rapidgator.net/file/f2485be233660f8d745d9c961e9136fa/z5ewu.Windows.Performance.Toolkit.Spyware.Detection.part2.rar.html]z5ewu.Windows.Performance.Toolkit.Spyware.Detection.part2.rar.html http://nitroflare.com/view/6382DB8A793EBC9/z5ewu.Windows.Performance.Toolkit.Spyware.Detection.part1.rar]z5ewu.Windows.Performance.Toolkit.Spyware.Detection.part1.rar http://nitroflare.com/view/13EE6FC93EF166D/z5ewu.Windows.Performance.Toolkit.Spyware.Detection.part2.rar]z5ewu.Windows.Performance.Toolkit.Spyware.Detection.part2.rar http://uploaded.net/file/571hszuw/z5ewu.Windows.Performance.Toolkit.Spyware.Detection.part1.rar]z5ewu.Windows.Performance.Toolkit.Spyware.Detection.part1.rar http://uploaded.net/file/i2hith1j/z5ewu.Windows.Performance.Toolkit.Spyware.Detection.part2.rar]z5ewu.Windows.Performance.Toolkit.Spyware.Detection.part2.rar https://www.bigfile.to/file/mJynqDJTTNHR/z5ewu.Windows.Performance.Toolkit.Spyware.Detection.part1.rar]z5ewu.Windows.Performance.Toolkit.Spyware.Detection.part1.rar https://www.bigfile.to/file/Dc7uUqJedpB2/z5ewu.Windows.Performance.Toolkit.Spyware.Detection.part2.rar]z5ewu.Windows.Performance.Toolkit.Spyware.Detection.part2.rar Links are Interchangeable - No Password - Single Extraction

Understanding Intrusion Detection Systems Training Video - Infinite Skills English | Size: 0.99 GB (1,059,256,402 Bytes) Category: CBTs Understanding Intrusion Detection Systems Training Video An outsider might be inside your network and ready to release attack traffic. A disgruntled employee might be inside your system and ready to delete files. You're a systems or network admin and it's your job to prevent these types of malicious events. Where do you begin? A good start is knowing with some certainty that the attackers are even present and a good intrusion detection system will do just that. In this video, security expert Ric Messier explains why intrusion detection systems are necessary, what they do, how they work, where to find them, and how to implement them. * Understand intrusion detection: Its meaning, its value, and how to implement it * Master the workings of host-based and network-based intrusion detection systems * Learn about network captures, cryptographic hashes, alerting, incident response, and more * Gain awareness of anomaly based and signature based intrusion detection systems * Learn to use open source intrusion detection systems like Snort, Suricata, and Bro * Understand how to perform file integrity checks using Tripwire and Samhain * Review multiple forms of built-into-the-OS IDS systems Download link: http://rapidgator.net/file/40acf49431bea1df4d2e52994e8c0fb6/ie6br.Understanding.Intrusion.Detection.Systems.Training.Video..Infinite.Skills.part1.rar.html]ie6br.Understanding.Intrusion.Detection.Systems.Training.Video..Infinite.Skills.part1.rar.html http://rapidgator.net/file/764fa2bf5a3fa9874ced41dd170fd23e/ie6br.Understanding.Intrusion.Detection.Systems.Training.Video..Infinite.Skills.part2.rar.html]ie6br.Understanding.Intrusion.Detection.Systems.Training.Video..Infinite.Skills.part2.rar.html http://nitroflare.com/view/1C171EA9F41ED83/ie6br.Understanding.Intrusion.Detection.Systems.Training.Video..Infinite.Skills.part1.rar]ie6br.Understanding.Intrusion.Detection.Systems.Training.Video..Infinite.Skills.part1.rar http://nitroflare.com/view/A4EE2C484F347FE/ie6br.Understanding.Intrusion.Detection.Systems.Training.Video..Infinite.Skills.part2.rar]ie6br.Understanding.Intrusion.Detection.Systems.Training.Video..Infinite.Skills.part2.rar http://uploaded.net/file/ye59e0pc/ie6br.Understanding.Intrusion.Detection.Systems.Training.Video..Infinite.Skills.part1.rar]ie6br.Understanding.Intrusion.Detection.Systems.Training.Video..Infinite.Skills.part1.rar http://uploaded.net/file/uxvwxdqe/ie6br.Understanding.Intrusion.Detection.Systems.Training.Video..Infinite.Skills.part2.rar]ie6br.Understanding.Intrusion.Detection.Systems.Training.Video..Infinite.Skills.part2.rar https://www.bigfile.to/file/U8qkdWxj3GnJ/ie6br.Understanding.Intrusion.Detection.Systems.Training.Video..Infinite.Skills.part1.rar]ie6br.Understanding.Intrusion.Detection.Systems.Training.Video..Infinite.Skills.part1.rar https://www.bigfile.to/file/KnvhxZxhWQ3V/ie6br.Understanding.Intrusion.Detection.Systems.Training.Video..Infinite.Skills.part2.rar]ie6br.Understanding.Intrusion.Detection.Systems.Training.Video..Infinite.Skills.part2.rar Links are Interchangeable - No Password - Single Extraction

Udemy - Face Detection -Master Open CV with Digital Image Processing English | MP4 | 1280x720 | 60 kbps | 44 KHz | 3 hours | 154 Mb Genre: eLearning Face Detection - Digital Image Processing and Open CV using C++. Best course for face detection and Open CV First of all let me tell you what is Open CV and what are the things that we can do using OpenCV. (If you are not familiar with Open CV), OpenCV is a open source C++ library for digital image processing and computer vision, which can be used to create real time face recognisation and using it with eMbedded robotics and micro controllers for purpose like differentiating a specific color from an image having various colors. Are you willing to become a programmer? Do you want to make softwares that actually sells? Do you want to present projects in your University and to score good marks? Do you wonder why you are not good at programming? Do you want to showcase your talent and present in front of your specific audience? Are you looking for getting projects as a freelancer but never got the opportunity? Do you want techniques and methods that will enhance your programming skills and more peoples would be appreciating you for your works? readmore Solution to all this we will cover in this course. "Few years back, I started learning programming and spent couple of months just to learn the basics. Then, for again a couple of months I spent my time learning advance of Open CV. Being in the same field for almost one year, I decided to start my own project. But I keep on stuck at various steps of my project as many of concepts were not cleared. I was not able to develop a simple software from the knowledge I gained. I was depressed and thinking to leave the programming. Then one day, I decided to give it one more try. I wrote down all the parts of my programming knowledge where I had weak concepts. I started visiting forums and posting my questions to sharpen my skills and doubt clearance. And again tried to create that project with fewer difficulties. I repeated the same method again and dig a lot. Now I got success, I am a professional programmer in C++ and OpenCV and now working with two companies." What you need is someone to teach you step by step every algorithm of OpenCV and C++, concepts which are widely used in programming and algorithms that are universal to each program. So that you can go forward without googling all day and night. Just 2 hours, you need only two hours to end this course and to become a master of Open CV and C++ advance. We have all the data collected from different resources at one place which includes : Real time face detection and object tracking. EMbed robotics and micro controllers. Differentiating specific colors from an image and video stream through webcam. Make projects like human detecting bots, color following bots, laser toy gun bots, bots playing football etc. And you can see the whole curriculum of the course under this section. Today you will have start up in OpenCV and C++ that will lead to make you a successful programmer. Today if you spend time watching your videos of this course then you don't need to google all time and collect resources. Yes, you could spend hours learning how to do it on google, and then you have to sort out the good from the bad information. And spend hundred of dollars taking private coaching that explain exactly how to do it, or you could buy all the information you need from this course for this little price. This course can be taken by anyone, as it includes section starting from beginners to advance step by step. The programming files includes comments on each line so that you won't have problem learning the program methodology. I will be updating it time to time with new projects and projects integrated with micro controllers and Arduino and projects on demand. Yes you can demand us a project that you are looking for and we will be creating and uploading it for you. No other course for OpenCV or Digital image processing is as simple as this and in this much of details. There is a summary page at the end of each section to sum up every topic under that section. You can ask me for help if you stuck or find any difficulty on understanding. I will put my best efforts into it. There is a 30 days money back guarantee also on this course, if in any case you don't like the course, then you can take the full refund from us. Hope to see you in the course. What are the requirements? Basic computer understanding What am I going to get from this course? Over 29 lectures and 2 hours of content! Installing OpenCV and setting up with MS Visual 2013 Understanding and Using OpenCV library function Face tracking (Real-time and also from image) Object Tracking (Real-time and also from image) Using it with Arduino (or other microcontroller) What is the target audience? 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Udemy - Face Detection -Master Open CV with Digital Image Processing MP4 | Video: 1280x720 | 60 kbps | 44 KHz | Duration: 3 Hours | 249 MB Genre: eLearning | Language: English Face Detection - Digital Image Processing and Open CV using C++. Best course for face detection and Open CV First of all let me tell you what is Open CV and what are the things that we can do using OpenCV. (If you are not familiar with Open CV), OpenCV is a open source C++ library for digital image processing and computer vision, which can be used to create real time face recognisation and using it with embedded robotics and micro controllers for purpose like differentiating a specific color from an image having various colors. Are you willing to become a programmer? Do you want to make softwares that actually sells? Do you want to present projects in your University and to score good marks? Do you wonder why you are not good at programming? Do you want to showcase your talent and present in front of your specific audience? Are you looking for getting projects as a freelancer but never got the opportunity? Do you want techniques and methods that will enhance your programming skills and more peoples would be appreciating you for your works? Read more: Solution to all this we will cover in this course. "Few years back, I started learning programming and spent couple of months just to learn the basics. Then, for again a couple of months I spent my time learning advance of Open CV. Being in the same field for almost one year, I decided to start my own project. But I keep on stuck at various steps of my project as many of concepts were not cleared. I was not able to develop a simple software from the knowledge I gained. I was depressed and thinking to leave the programming. Then one day, I decided to give it one more try. I wrote down all the parts of my programming knowledge where I had weak concepts. I started visiting forums and posting my questions to sharpen my skills and doubt clearance. And again tried to create that project with fewer difficulties. I repeated the same method again and dig a lot. Now I got success, I am a professional programmer in C++ and OpenCV and now working with two companies." What you need is someone to teach you step by step every algorithm of OpenCV and C++, concepts which are widely used in programming and algorithms that are universal to each program. So that you can go forward without googling all day and night. Just 2 hours, you need only two hours to end this course and to become a master of Open CV and C++ advance. We have all the data collected from different resources at one place which includes : Real time face detection and object tracking. Embed robotics and micro controllers. Differentiating specific colors from an image and video stream through webcam. Make projects like human detecting bots, color following bots, laser toy gun bots, bots playing football etc. And you can see the whole curriculum of the course under this section. Today you will have start up in OpenCV and C++ that will lead to make you a successful programmer. Today if you spend time watching your videos of this course then you don't need to google all time and collect resources. Yes, you could spend hours learning how to do it on google, and then you have to sort out the good from the bad information. And spend hundred of dollars taking private coaching that explain exactly how to do it, or you could buy all the information you need from this course for this little price. This course can be taken by anyone, as it includes section starting from beginners to advance step by step. The programming files includes comments on each line so that you won't have problem learning the program methodology. I will be updating it time to time with new projects and projects integrated with micro controllers and Arduino and projects on demand. Yes you can demand us a project that you are looking for and we will be creating and uploading it for you. No other course for OpenCV or Digital image processing is as simple as this and in this much of details. There is a summary page at the end of each section to sum up every topic under that section. You can ask me for help if you stuck or find any difficulty on understanding. I will put my best efforts into it. There is a 30 days money back guarantee also on this course, if in any case you don't like the course, then you can take the full refund from us. Hope to see you in the course. What are the requirements? Basic computer understanding What am I going to get from this course? Over 29 lectures and 2 hours of content! Installing OpenCV and setting up with MS Visual 2013 Understanding and Using OpenCV library function Face tracking (Real-time and also from image) Object Tracking (Real-time and also from image) Using it with Arduino (or other microcontroller) What is the target audience? Interested in openCV Using it with AVR Microcontollers http://rapidgator.net/file/3ecbdff98cd1fcb60d7f61963cee65c4/1jtid.Udemy..Face.Detection.Master.Open.CV.with.Digital.Image.Processing.part1.rar.html http://rapidgator.net/file/a96727cce45adc6c89a2e36db980198f/1jtid.Udemy..Face.Detection.Master.Open.CV.with.Digital.Image.Processing.part2.rar.html http://rapidgator.net/file/673ac2fae097067802196588e588f802/1jtid.Udemy..Face.Detection.Master.Open.CV.with.Digital.Image.Processing.part3.rar.html http://www.nitroflare.com/view/F2065533D403E9A/1jtid.Udemy..Face.Detection.Master.Open.CV.with.Digital.Image.Processing.part1.rar http://www.nitroflare.com/view/420A4E80A32D9B8/1jtid.Udemy..Face.Detection.Master.Open.CV.with.Digital.Image.Processing.part2.rar http://www.nitroflare.com/view/F2CB30538F7E4F7/1jtid.Udemy..Face.Detection.Master.Open.CV.with.Digital.Image.Processing.part3.rar http://uploaded.net/file/20zqkyya/1jtid.Udemy..Face.Detection.Master.Open.CV.with.Digital.Image.Processing.part1.rar http://uploaded.net/file/wqlyu0yz/1jtid.Udemy..Face.Detection.Master.Open.CV.with.Digital.Image.Processing.part2.rar http://uploaded.net/file/d44yl8eu/1jtid.Udemy..Face.Detection.Master.Open.CV.with.Digital.Image.Processing.part3.rar http://www.uploadable.ch/file/TGF6w6TJW4Ah/1jtid.Udemy..Face.Detection.Master.Open.CV.with.Digital.Image.Processing.part1.rar http://www.uploadable.ch/file/6cqgFS6B7Qum/1jtid.Udemy..Face.Detection.Master.Open.CV.with.Digital.Image.Processing.part2.rar http://www.uploadable.ch/file/EQZ4JaPQF8x4/1jtid.Udemy..Face.Detection.Master.Open.CV.with.Digital.Image.Processing.part3.rar