Popular GitHub Repositories for Accident Severity

Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)

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

Abnormal Human Behaviors Detection/ Road Accident Detection From Surveillance Videos/ Real-World Anomaly Detection in Surveillance Videos/ C3D Feature Extraction

[IV2024] MultiCorrupt: A benchmark for robust multi-modal 3D object detection, evaluating LiDAR-Camera fusion models in autonomous driving. Includes diverse corruption types (e.g., misalignment, miscalibration, weather) and severity levels. Assess model performance under challenging conditions.

Accident Detection Model using Deep Learning, OpenCV, Machine Learning, Artificial Intelligence.

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

Research project on building and evaluating deep learning models for landslides detection on satellite images

Perform a survival analysis based on the time-to-event (death event) for the subjects. Compare machine learning models to assess the likelihood of a death by heart failure condition. This can be used to help hospitals in assessing the severity of patients with cardiovascular diseases and heart failure condition.

This is the implementation code for the paper, "A Dynamic Spatial-temporal Attention Network for Early Anticipation of Traffic Accidents"

Severity scoring and exploit categorisation for vulnerability reports using machine-learning tools.

??A Centralized WebApp to Ensure Road Safety by checking on with the activities of the driver and activating label generator using NLP.

The AI model recognizes burned wounds, determines their severity, and shows the user the severity of the wounds and the first aid manual.

LLM-powered analyzer identifying security events, errors, and anomalies in logs, visualized via Elasticsearch.

Code of our paper "Method-Level Bug Severity Prediction using Source Code Metrics and LLMs" which is accepted to ISSRE 2023.

AI-Depression Detector uses Deep Learning model which is built on top of CNN architecture to analyse patient expressions and input to known the level of severity of the depression . It also uses PHQ-9 to get more insight from the patients.

Web app to Predict of US traffic accidents severity based on weather conditions like visibility, temperature and weather categories like rain, snow, foggy etc as well as based on US location and the day of the week.

?? ? Contains Matlab codes used for implementation of acceleration signal processing algorithm on smartphones for accident detection. ??

App that detects severity of Diabetic Retinopathy using TensorflowLite model trained from scratch in Google Colab notebook.

?? Accident damage estimation for insurance companies using the CatBoost algorithm. ?? This advanced technique utilizes machine learning to provide accurate estimates for assessing damages caused by accidents. ?? Enhance efficiency and accuracy in insurance claim processes with the power of CatBoost! ??

BimaRakshak AI is an AI-powered motor insurance risk assessment platform that uses real-time driving behavior and machine learning to offer fair insurance premiums, detect accident-prone zones, and promote road safety.