AI-Driven Freezing of Gait (FOG) detection in Parkinson's disease using machine learning and sensor data analysis.
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Updated
May 18, 2024 - Jupyter Notebook
AI-Driven Freezing of Gait (FOG) detection in Parkinson's disease using machine learning and sensor data analysis.
A deep learning-based vehicle detection system for foggy and low-visibility environments using YOLO and image enhancement techniques. Designed for intelligent transportation systems, autonomous driving, and traffic monitoring.
Personalized FOG (Freezing of Gait) Detection System for Parkinson's Disease using Multimodal Biosignals (sEMG, EEG, IMU) and Hybrid Deep Learning.
Object detection in foggy road scenes using pretrained Faster R-CNN (ResNet50-FPN) in PyTorch, analyzing model robustness under low-visibility conditions.
YOLOv8?????????????? | ????/??/??????? | ?????? | ??????? | Flask + Vue + MySQL
An IoT-integrated hybrid deep learning system that detects vehicles in foggy environments, estimates fog density, and recommends safe driving speeds using YOLOv8, Faster R-CNN, and ThingSpeak.
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