This module uses a pre-trained Faster R-CNN (ResNet-50 FPN) for object detection on images. It processes the image, filters high-confidence predictions (score > 0.8), and visualizes the results using ...

This project was part of Advance Machine Learning course on deep learning. A model was developed in R using state-of-art techniques in deep learning i.e. CNN and identified objects in any given images ...

Abstract: Using OpenCV, this research compares the performance of deep learning with standard computer vision approaches for detecting object in photos and videos. Recognizing and localizing objects ...

OpenCV offers various methods for image segmentation and object detection. For segmentation, techniques like thresholding, contour detection, and watershed segmentation are utilized to partition ...

The system comprises the UAV detection module and the UAV tracking module. The detection module design is based on a novel CNN implementation running on FPGA’s PL fabric, together with a tracking ...