IEEE

Word Level Ethiopian Sign Language Recognition Using Hybrid CNN-LSTM Model

Abstract: In this research, we propose a hybrid CNN and LSTM model for word-level Ethiopian sign language recognition. The recognition system has four major components: preprocessing, feature ...
IEEE

ST-Gesture: Spatio-Temporal Feature Extraction Network for Gesture Recognition Based on Attention Mechanism

Abstract: Gesture recognition, a crucial technology in human-computer interaction, finds applications across various domains, including smart homes, automotive driver assistance systems, and more.
IEEE

Recognition of Excavator Operation Objects Based on BO-CNN-LSTM-Adaboost

Abstract: With the continuous development of engineering machinery technology, excavators, as a key engineering equipment, have played an important role in the fields of construction and mining.
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

IVEX-WA and IVEX-MetaStack Ensemble Models: A Transfer Learning Approach for Still-Image Human Action Recognition With XAI Visualization

Abstract: Human action recognition (HAR) using deep learning approaches has significantly improved our lives, including elderly care, child monitoring, and sports analytics, particularly where human ...
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 ...
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

Research on Communication Signal Recognition based on CNN-LSTM Neural Networks

Abstract: This paper addresses the issue of degraded accuracy in traditional communication signal recognition under low Signal-to-Noise Ratio (SNR) environments by proposing a Convolutional Neural ...