IEEE

Automated Face Recognition System Using Convolutional Neural Network

Abstract: The research is devoted to the development of an automated face recognition system based on a convolutional neural network (CNN). The proposed system uses modern methods of image ...
IEEE

Vanillanet-BGA: An Accurate Detection Network for Strip Steel Surface Defects Based on Vanillanet and Feature Fusion Embedded Attention Mechanism

Abstract: The exponential growth of modern industrial production systems, coupled with escalating quality requirements in manufacturing sectors, has stimulated substantial research interest in ...
IEEE

Development and Validation of Feature-Based Machine Learning for ECG Artifact Detection and Classification

Abstract: ECG signals are vital for diagnosing cardiovascular diseases, but artifacts like power line interference, baseline wander, and motion artifacts hinder accurate interpretation. This study ...
IEEE

The ACGAN-AOA-CNN-BiGRU Model for Network Intrusion Detection

Abstract: Addressing the dual challenges of class imbalance and manual hyperparameter tuning in network intrusion detection, this paper proposes a CNN-BiGRU detection model integrating Adversarial ...
IEEE

Feature Fusion Based on Temporal-Spatial Attention Model for Automatic Epileptic Seizure Detection

Abstract: Epilepsy, a widespread neurological disorder, poses challenges for timely seizure detection due to complex EEG signals, noise, and data imbalance. We propose the Temporal-Spatial Fusion ...
IEEE

DAS-Based Perimeter Intrusion Detection Using 2D-CNN With SKAttention Mechanism

Abstract: Distributed fiber optic sensing technology has been extensively applied in the field of perimeter security. The distributed acoustic sensing (DAS) system driven by a deep learning ...
IEEE

A Lightweight Detection Method for Atrial Fibrillation Using Clustering Feature Extraction on Wearable Devices

Abstract: Atrial fibrillation (AF) is a common arrhythmia. The accuracy and efficiency of detection for wearable electrocardiogram (ECG) devices are limited by noise interference and poor data quality ...
IEEE

A Novel Alzheimer’s Disease Classification Framework Integrating 3D CNN With Bidirectional Feature Pyramid Network and Vision Transformers

Abstract: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that severely affects memory and cognitive function, underscoring the need for accurate and early diagnostic tools. Deep ...
IEEE

TCINet: Transformer–CNN Interaction Network for Space Noncooperative Object Saliency Detection

Abstract: Space noncooperative object detection (SNCOD) is an essential part of space situation awareness. The localization and segmentation capabilities of the salient object detection (SOD) method ...
IEEE

FLIA-YOLO for Contraband Detection with High-Low Frequency Feature Enhancement and Multi-Scale Interactive Attention

Abstract: In contraband detection, problems such as small targets, occlusions, and multi-scale feature extraction seriously affect detection performance. To this end, we proposed the FLIA-YOLO ...
IEEE

ELG-YOLO: Multi-Scale Feature Fusion and Attention Mechanisms for Enhanced Steel Surface Defect Detection

Abstract: Surface defect detection is essential for industrial product quality assurance. To address challenges including large-scale variations, diverse defect morphologies, high inter-class ...
IEEE

Enhancing CNN-Based Motion Sickness Detection using EEG Signals Weighted by Motion Sickness Dose Value

Abstract: With the advancement of autonomous driving technologies, passengers increasingly engage in non-driving activities. However, these activities are often limited by motion sickness (MS), which ...