By leveraging diffusion models, low-resolution MRI scans are upgraded to high-resolution images. The model is trained on image pairs, enabling it to learn noise reduction and generate clearer, more detailed MRI scans. Code : https://github.com/chichonnade/MRI-Super-Resolution/tree/main Demo : Low Resolution 1.5T to High Resolution 3T MRI Overview Latest diffusion models have shown promising results in super-resolution tasks. This project aims to leverage these models to enhance the resolution of MRI images....
This project improves object detection in autonomous vehicles by integrating radar and camera data. The pipeline processes and aligns data from both sensors, detects objects using YOLO, and clusters radar points with DBSCAN. The merged results offer a precise and reliable view of the vehicle’s surroundings, enhancing detection accuracy and safety in complex environments. Code : https://github.com/chichonnade/ZendarComputerVisionCapstone Demo Driving scene showing obstacles detected by our pipeline Raw data from radar and camera sensors Motivation Data Fusion Validation:...