IEEE

An Attention-Enhanced 3D-CNN Framework for Spectrogram-Based EEG Analysis in Epilepsy Detection

Abstract: Epilepsy is a widespread neurological disorder affecting approximately 50 million individuals globally, with a disproportionately high burden in low- and middle-income countries. It is ...
IEEE

MCGC-Net: Multi-scale Controllable Graph Convolutional Network on Music Emotion Recognition

Abstract: This paper introduces a novel dynamic graph learning approach for frequency graphs, underpinned by a suite of baseline methodologies and the Multi-scale Controllable Graph Convolutional ...
IEEE

SDR-Based Metal Classification Using Spectrogram Images from Micro-Doppler Signatures

Abstract: Metallic materials such as brass, copper, and aluminum are used in numerous applications, including industrial manufacturing. The vibration characteristics of these objects are unique and ...
IEEE

Recognition of Eye Diseases Based on Convolutional Neural Networks (CNN)

Abstract: In this study, a convolutional neural network (CNN)-based method for eye disease recognition is proposed, aiming to identify multiple common eye diseases through automatic analysis of fundus ...
IEEE

Toward Real-World ECG-Based Human Activity Recognition: Optimal Window Size and Subject-Independent 1-D CNN Approach

Abstract: Human activity recognition (HAR) is essential for advancing healthcare, fitness, and patient monitoring because it provides critical insights into human physical movements. This study ...
GitHub

AhmedEl-diasty/Human-Activity-Recognition-CNN-LSTM

This project implements a hybrid deep learning model combining Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks for human activity recognition using sensor data from ...
IEEE

Human Motion Recognition Based on Videos and Radar Spectrograms in Cross-Target Scenarios

Abstract: Multisensor fusion combines the benefits of each sensor, resulting in a thorough and reliable motion recognition even in challenging measurement environments. Meanwhile, even with the ...
IEEE

Human Action Recognition Based on Bimodal Data and Spationtemporal Features Using UWB MIMO Radar

Abstract: Human action recognition (HAR) methods based on ultra-wideband (UWB) multiple-input–multiple-output (MIMO) radar have demonstrated substantial potential in complex environments. However, the ...
IEEE

An SAGPSO-CNN Approach for Supervised Fault Classification in MVdc Shipboard Power Systems

Abstract: All-electric ships (AESs) utilizing medium-voltage dc (MVdc) shipboard power systems (SPSs) rely on a limited number of generators to supply power to propulsion units and onboard loads. To ...
IEEE

Reaction Rumble : A Facial Expression Recognition Application using CNN

Abstract: However, CNNs and SSD MobileNet serve a slightly different plane of purpose. Their main adaptability lies in the differentiation of features of face landmarks at various levels, such as eyes ...
IEEE

Audio-Visual Speech and Gesture Recognition using Dual Sampling Residual Attention CNN on Mobile Devices

Abstract: Speech and gesture recognition has become a critical feature in this day’s applications and is critical in accessibility and learning and human-computer interfaces. However, real-scene ...
IEEE

Mixed Intrusion Vibration Signal Recognition Based on Fiber Bragg Grating and RL-KAN-CNN

Abstract: Fiber Bragg Grating (FBG) sensing systems have demonstrated strong potential for distributed vibration monitoring, yet recognizing mixed intrusion events remains challenging due to the ...