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.

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