Скачать или смотреть Object Detection and Its Applications

This video explains the technique of object detection for locating instances of objects in images or videos. It covers various real-life applications and use cases of object detection. It differentiates object detection from image classification along with the different types of models like one stage and two stage models used for detecting objects with the help of bounding boxes. The architecture of CNN to perform such tasks is also elaborated. It discusses how single-stage (YOLO and SSD) and two-stage (RCNN, Fast RCNN and Faster RCNN) approaches are different from each other and their pros and cons in the context of datasets with use cases. Thus, this video gives a comprehensive understanding for anyone who's willing to leverage object detection to solve significant problems in Machine Learning and delve into projects related to the same.
The upcoming video will demonstrate how to build and set up a custom object detection model in Python using the YoloV4 model.

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