YOLOv4 Object Detection Crash Course | YOLO v4 how it works and how to build it | Introduction
This video titled "YOLOv4 Object Detection Crash Course | YOLO v4 how it works and how to build it | Introduction" gives the introduction of Yolo
V4 object detection framework i.e. what exactly it is, a brief explanation of various components of its architecture, different use cases of it as well as a demo of it at the end of the video. YOLO stands for "You Look
Only Once". It is a state of art real-time object detection framework. It uses a Convolutional Neural network to detect objects in the image or video. YOLO V4 version is very fast, more accurate and can process any video 65
fps. It is a very good choice when you need real-time detection, without loss of too much accuracy. YOLO framework is really good in terms of detecting multiple objects in an image or video hence not only good at predicting different classes in the image but also their actual location.
Yolo v4 Paper : https://arxiv.org/abs/2004.10934
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#YOLOv4 #ObjectDetection #LabelImages
