IEEE

MLAR-Net: A Multilevel Attention-Based ResNet Module for the Automated Recognition of Emotions Using Single-Channel EEG Signals

Abstract: Human emotion recognition is important as it finds applications in multiple domains such as medicine, entertainment, and military. However, accurately identifying emotions remains ...
Microsoft

A CNN-Based Approach for Automatic License Plate Recognition in the Wild

In this paper, we address automatic license plate recognition (ALPR) in the wild. Such an ALPR system takes an arbitrary image as input and outputs the recognized license plate numbers. In the ...
IEEE

Multimodal Fusion of Speech and Action Recognition for IoT Device

Abstract: Developments in deep learning techniques have opened up novel possibilities in the multimodal data fusion field. However, there is a significant gap in the capability of deep learning ...
IEEE

Emotion Recognition from Speech Signals Using Hybrid CNN Model

Abstract: The fast growth of internet and communications networks has drastically enhanced data transport, allowing tasks like Speech Emotion Recognition (SER), an essential aspect of human-computer ...
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

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

Stress Classification from ECG Signals Using Vision Transformer

Abstract: Vision Transformers have shown tremendous success in numerous computer vision applications; however, they have not been exploited for stress assessment using physiological signals such as ...
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 ...