IEEE

Channel–Spatial Aligned Global Knowledge Distillation for Underwater Acoustic Target Recognition

Abstract: Knowledge distillation (KD) is a predominant technique to streamline deep-learning-based recognition models for practical underwater deployments. However, existing KD methods for underwater ...
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

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 ...
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 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

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 ...
IEEE

Federated Quantum Kernel-Based Long Short-Term Memory for Human Activity Recognition

Abstract: In this work, we introduce the Federated Quantum Kernel-Based Long Short-term Memory (Fed-QK-LSTM) framework, integrating the quantum kernel methods and Long Shortterm Memory into federated ...
IEEE

Intelligent Fault Diagnosis of Motor Bearings Based on Dual-Branch Depthwise Separable CNN with Acoustic-Vibration Signal Fusion

Abstract: The intelligent diagnosis of motor bearings under complex working conditions presents significant challenges, including insufficient feature extraction, limited reliability of ...