IEEE

A Time-Efficient Deep Learning Approach for Real-Time EEG-Based Driver Drowsiness Detection

Abstract: Drowsy driving significantly contributes to road accidents globally, underscoring the need for reliable real-time drowsiness detection systems. While various approaches exist, ...
IEEE

Advancing Road Safety: A CNN-Based Semi-Supervised Learning Approach for Drivers' Drowsiness Detection

The National Safety Council (NSC) has reported that each year, driver fatigue is responsible for 100,000 accidents, 71,000 injuries, and 1,550 fatalities, often manifesting as drowsiness. Most current ...
IEEE

BinShoo: Binary Code Similarity Detection Using Optimized Function Embedding and Siamese Neural Network

Abstract: Binary code similarity detection (BCSD) is important for cybersecurity, software analysis, and security research, helping to identify malware, vulnerabilities, and duplicate code as well as ...
IEEE

IoT Based Driver Drowsiness Detection Using Convolutional Neural Network

Abstract: Drowsiness while driving is a core threat to global safety on roads, resulting in significant traffic accidents and fatalities. Efficient strategies to combat drowsy driving are an emerging ...
IEEE

Magnetocardiography Detection and Source Localization From Multiple Sources Using Magnetoimpedance Principle in Controlled Environment

Abstract: Recent advances in non-invasive cardiac imaging techniques have highlighted the potential of Magnetocardiography (MCG) as a powerful diagnostic tool. However, existing approaches face ...
IEEE

Code Comment Inconsistency Detection and Rectification Using a Large Language Model

Abstract: Comments are widely used in source code. If a comment is consistent with the code snippet it intends to annotate, it would aid code comprehension. Otherwise, Code Comment Inconsistency (CCI) ...
IEEE

A Dual Convolution Hybrid Multi-Model for Code Vulnerability Detection

Abstract: Existing vulnerability detection models can typically detect only a limited range of vulnerabilities. As the variety of vulnerabilities increases, performance will be reduced. Graph ...
IEEE

A Lightweight MobileNetV3-FPN Framework for Driver Drowsiness Detection

Abstract: Driver drowsiness remains a major cause of traffic accidents, requiring a drowsiness detection system to achieve high accuracy and real-time inference speed. To overcome these challenges, we ...
IEEE

A Low-Cost IoT Solution for Real-Time Driver Drowsiness Detection using Eye-Blink sensor

Abstract: Drowsy driving is a major cause of road accidents, often leading to severe injuries or fatalities. This paper presents an IoT-based driver drowsiness detection system that monitors eye blink ...
IEEE

Driver Distraction Detection System with Categorized Alerting based on SVM and PCA Optimization

Abstract: The road accident scenario in India can be understood by simple statistics, and that every year more than 1.5 Lakh people lose their lives on the road. This is like crashing a jumbo jet ...
IEEE

EEG-Based Driver Fatigue Detection with Frequency–Spatial Attention and Mamba2 Temporal Modeling

Abstract: Driver fatigue is a significant research topic in the field of traffic safety. How to utilize electroencephalogram (EEG) signals to rapidly and accurately identify a driver's fatigue state ...
GitHub

Pull requests: mobinyousefi-cs/Drowsy-Driver-Detection-MATLAB

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.