Multi-class wildlife classification using YOLOv5, YOLO v7 and Detectron2- Faster RCNN

There has been an average 68% decline in animal populations since 1970. In order to better understand and monitor the decline in wildlife biodiversity, ecologists often deploy what are known as camera traps — heat- or motion-activated static cameras placed in the wild — and then use machine learning to process the data collected. Below are a few examples of how camera traps have been used to monitor animal populations: ● Identifying and classifying species is an essential first step in determining the long-term viability of animals and how our actions may affect them. ● It aids people in recognizing predators and non-predatory animals, both of which might pose a significant threat to local species and humans. <a href="https://medium.com/@amritangshu.mukherjee/multi-class-wildlife-classification-using-yolov5-yolo-v7-and-detectron2-faster-rcnn-b8423ffdbf6b">Visit Now</a>