Occlusion Removal Using Deep Autoencoder
Research Project | 2023
Combined object detection and tracking models to enhance detection accuracy under occlusion.
Key Achievements
- Utilized bounding box prediction and motion tracking to improve performance
- Developed algorithms to handle partial object occlusion
- Applied deep autoencoders for feature reconstruction
Technologies Used
- Computer Vision
- Autoencoders
- Object Tracking
- Deep Learning