The project introduces a Multi-Stage Traffic Anomaly Analysis Framework for identifying and analyzing urban traffic congestion, particularly in Dhaka. Originally utilizing Faster R-CNN and DBSCAN, it has been upgraded to state-of-the-art YOLOv9e and YOLOv10l models for enhanced accuracy and efficiency.

This repository contains the code and results for a project focused on the computational analysis of sexual dimorphism in the Catopsilia pomona using visual classifiers (CNN, ResNet50, YOLO11n-cls). The project aims to accurately classify the sex of butterflies based on wing images and provides insights into the key visual features.

ExplainableTrack — an explainable, interpretable toolkit for object tracking with visualizations.

Advanced AI Explainability for computer vision.All the non Gradient Methods.