Popular GitHub Repositories for Vital Signs

rPPG-Toolbox: Deep Remote PPG Toolbox (NeurIPS 2023)

Implementation of Single Shot MultiBox Detector in TensorFlow, to detect and classify traffic signs

Official implementation for "Stable Flow: Vital Layers for Training-Free Image Editing" [CVPR 2025]

SafeDriveVision is a computer vision project aimed at enhancing road safety. This project leverages deep learning models to detect and alert in real-time the dangerous behaviors of drivers, such as using a phone while driving or showing signs of drowsiness.

In this project, I used Python and TensorFlow to classify traffic signs. Dataset used: German Traffic Sign Dataset. This dataset has more than 50,000 images of 43 classes. I was able to reach a +99% validation accuracy, and a 97.3% testing accuracy.

This project implements a functional motion planning stack for autonomous vehicles to avoid both static and dynamic obstacles while tracking the center line of a lane, while also handling stop signs.

This repository contains the code of our winning solution for the Shared Task on Detecting Signs of Depression from Social Media Text at LT-EDI-ACL2022.

This app recognises 3 hand signs - fist, high five and victory hand [ rock, paper, scissors basically :) ] with live feed camera. It uses a HandSigns.mlmodel which has been trained using Custom Vision from Microsoft.

FactorizePhys: Matrix Factorization for Multidimensional Attention in Remote Physiological Sensing [NeurIPS 2024]

Using synthetic data in combination with Deep Learning, to determine if a system can be made that will be able to recognise and classify correctly real traffic signs.

ICAIF 2021 Paper "A Machine Learning Approach to Detect Early Signs of Startup Success"

Deep neural networks and convolutional neural networks to classify German traffic signs.

In this project, we build a simple federated deep learning model (i.e., LeNet model) that classifies 62 differents Belgian Traffic Signs.

Python toolbox for plotting, processing, and interactively labeling vital data

This consists in using a variety of social networks data, including both images and texts, to detect early signs of depression.

AdvSV stands as the first dataset developed specifically for evaluating Speaker Verification (SV) systems against adversarial attacks. It aims to benchmark the robustness of ASV models in the face of such attacks and offers vital resources for researchers to explore the characteristics of adversarial and replay attacks in this domain.

Classification, Object Detection, Adversarial Attack of Chinese Traffic Signs // 中式交通标志图片的分类、目标检测、对抗性攻击

Our project uses state-of-the-art deep learning techniques to tackle a vital medical task: polyp segmentation from colonoscopy images. We harness the Unet++ architecture and a robust tech stack to precisely detect and isolate polyps, advancing healthcare diagnostics and patient care. ??

This repository contains a transformer-based model for real-time American Sign Language (ASL) recognition. The model leverages transformer architecture to interpret ASL gestures and utilizes the Gemini-Pro LLM API for constructing sentences from recognized ASL signs.

Multi-Modal Multi-Task Remote Physiological Sensing