GitHub - shag1802/Object_Detection_and_Tracking_System: Our project aims to develop an advanced system for object detection and tracking using cutting-edge deep learning techniques. Leveraging state-of-the-art algorithms such as YOLO (You Only Look Once), Faster R-CNN (Region-based Convolutional Neural Networks), SORT (Simple Online and Real-Time Tracking), and DeepSORT (Deep Learning-Based SORT)

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Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
3a.ipynb		3a.ipynb
3b_Bike_vs_Horses.ipynb		3b_Bike_vs_Horses.ipynb
3b_STL10.ipynb		3b_STL10.ipynb
3d_(Faster-RCNN+DeepSort).ipynb		3d_(Faster-RCNN+DeepSort).ipynb
3d_(Faster-RCNN+SORT).ipynb		3d_(Faster-RCNN+SORT).ipynb
3d_(YOLO+DeepSort).ipynb		3d_(YOLO+DeepSort).ipynb
3d_(YOLO+SORT).ipynb		3d_(YOLO+SORT).ipynb
VR_Mini_Project_Report.pdf		VR_Mini_Project_Report.pdf

About

Our project aims to develop an advanced system for object detection and tracking using cutting-edge deep learning techniques. Leveraging state-of-the-art algorithms such as YOLO (You Only Look Once), Faster R-CNN (Region-based Convolutional Neural Networks), SORT (Simple Online and Real-Time Tracking), and DeepSORT (Deep Learning-Based SORT)