This project aims to develop an intelligent system using computer vision to identify individual jaguars by their unique facial and body patterns. A Vision Transformer (ViT) and advanced self-attention models will be used for segmentation and classification, with fine-tuned embeddings to enhance accuracy. The system will aid zoologists in tracking jaguars, especially after natural disasters, and will be deployed as an API for practical use.

In this talk, we will share insights into the use of ML techniques, such as object detection and classification, to improve video meetings on our Cisco devices. We'll discuss our wide range of ML models and their respective use cases. The session will include a focused examination of our head detection model, detailing the fundamental principles and demonstrating the specific functionalities it facilitates to refine the video meeting experience.