Popular GitHub Repositories for Fatigue

A real-time drowsiness detection system for drivers, which alerts the driver if they fall asleep due to fatigue while still driving. The computer vision algorithm used for the implementation uses a trifold approach to detect drowsiness, including the measurement of forward head tilt angle, measurement of eye aspect ratio (to detect closure of eyes) and measurement of mouth aspect ratio (to detect yawning).

Eye state classification using OpenCV and DLib to estimate Percentage Eye Closure (PERCLOS) and alert a drowsy person (such as a driver).

Comparing driver drowsiness detection with CNN + MobileNetV2 vs YOLOv11 for real-time accuracy and efficiency ??. Exploring both deep learning models to prevent fatigue-related accidents ??.

Neural architecture search framework based on reinforcement learning:"A Novel Approach to Detecting Muscle Fatigue Based on sEMG by Using Neural Architecture Search Framework"

Real-time driver drowsiness detection system using computer vision, OpenCV, and MediaPipe face mesh. Monitors eye movements and calculates Eye Aspect Ratio (EAR) to detect fatigue, providing immediate visual alerts for enhanced driving safety.

Field research exposing how LLM safeguards collapse under polite, persistent interaction. Includes full report, metrics, session logs, and the AION conditioning protocol.

A machine-learning based gaming session manager that recommends playtime based on fatigue and stress levels.

A Pygame simulation of emergent intelligence in an ant colony, governed by simple physical rules and a novel 'Mental Fatigue' panic mechanism to escape dynamic loops.

LexiAI is an AI assistant prototype focused on hyper-personalized recommendations, combating 'decision fatigue' by building a 'Virtual Persona' that learns user preferences, including specific negative filters. This project is built with 'Ethical Guardrails', respecting mental health and avoiding emotional dependency.

An AI-powered assistant designed to reduce decision fatigue by automating daily choices in outfit planning, meal planning, and task prioritization. Using the o1 API, it streamlines routine decisions, helping users save time and mental energy.

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