Published 12/2024
Created by Maria Khalid
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 10 Lectures ( 54m ) | Size: 1.23 GB
Master Object Detection with YOLO in C#: Build Real-Time AI Applications using YOLO, Tiny YOLO and NMS
What you’ll learn
Master YOLO and Tiny YOLO integration in C# for real-time object detection.
Implement Non-Maximum Suppression (NMS) to enhance detection accuracy and efficiency.
Build security monitoring and AI-powered image recognition apps using YOLO.
Optimize object detection workflows for speed and accuracy with Tiny YOLO.
Requirements
Basic Programming Knowledge: Familiarity with C# programming is recommended, but beginners can follow along with some effort. Visual Studio: Students should have Visual Studio installed and know basic project setup. Windows OS: The course uses Windows-based tools and frameworks for development. Interest in AI and Object Detection: A passion for learning about YOLO, Tiny YOLO, and real-time AI applications will be beneficial.
Description
Welcome to “Mastering Object Detection with YOLO: Real-Time Object Detection in C# a hands-on, comprehensive course designed to empower you with the skills and knowledge to leverage YOLO (You Only Look Once) for real-time object detection. This course is ideal for developers, data scientists, and AI enthusiasts who want to delve into the exciting world of object detection.Starting with the basics, you’ll grasp the importance of object detection and why YOLO stands out among other methods. We’ll guide you through designing an efficient object detection project, covering the essential tools, libraries, and setup needed for a smooth development experience.You will learn how to load the YOLO model into your application, understanding its structure and components, such as Darknet, weights, and configuration files. The course will also walk you through implementing video capture functionalities, enabling you to handle video streaming and frame processing effectively.In the core implementation phase, you’ll master capturing and processing video frames, followed by running object detection using the YOLO model. You’ll learn how to visualize bounding boxes around detected objects, making your application both functional and visually intuitive.Optimization techniques such as Non-Maximum Suppression (NMS) will be covered to enhance detection accuracy by eliminating redundant bounding boxes. For those seeking faster performance, the course introduces Tiny YOLO, providing insights into integrating it for real-time detection without compromising speed and accuracy.By the end of this course, you will have developed a fully functional object detection application, well-optimized for performance. Enroll now to transform your AI capabilities and achieve mastery in object detection with YOLO!
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