LibCity: An Open Library for Urban Spatial-temporal Data Mining

Summary of open source code for deep learning models in the field of traffic prediction

codes of Deep Spatio-Temporal Graph Convolutional Network for Traffic Accident Prediction

[IEEE T-ITS] MG-TAR: Multi-view Graph Convolutional Networks for Traffic Accident Risk Prediction

[WWW-21] DF-TAR: A Deep Fusion Network for Citywide Traffic Accident Risk Prediction with Dangerous Driving Behavior

M-LibCity: An Open Source Library for Urban Spatio-temporal Prediction Models Based on MindSpore

The fficial implementation of [TCSVT2025] A Multi-modal Architecture with Spatio-Temporal-Text Adaptation for Video-based Traffic Accident Anticipation https://ieeexplore.ieee.org/abstract/document/10933925/

Deep learning–based anomaly detection in egocentric traffic videos using ConvAE reconstruction and VideoMAE transformer classification.

Nutshell is an Web Application, Designed for Karnataka State Police to Predict and analysis Accidents

A web-based machine learning application built with Django that classifies traffic accident images using a Naive Bayes algorithm. The system analyzes uploaded images and categorizes them into three severity levels: severe accidents, moderate accidents, and no accidents.

Nutshell is an Web Application, Designed for Karnataka State Police to Predict and analysis Accidents

This study focuses on traffic accident prediction in Bangladesh, aiming to analyze road accident data to identify key factors contributing to crashes and develop predictive models.