IEEE

Real-Time Fall Detection With Hybrid CNN-LSTM Using IWR6843AOP FMCW Radar

Abstract: Falls are a leading health risk for the elderly, highlighting the need for accurate and unobtrusive monitoring systems. Traditional camera-based approaches often raise privacy concerns, ...
IEEE

A Comparative Study for Yemeni Poets Detection Using TEXT-CNN and RNN-LSTM Text Classification

Abstract: The growing prevalence of internet usage has led to a substantial capacity in textual data. Text classification is an essential field in natural language processing (NLP). It differs in ...
IEEE

Spatio-Temporal Deep Neural Modelling for Climate Anomaly Detection using CNN-LSTM Networks

Abstract: When it comes to studying environmental problems, it is growing increasingly vital to discover climatic anomalies and measure temperature changes, particularly in areas like Ethiopia, where ...
IEEE

Smart Surveillance: Real-Time Shoplifting Detection Using Deep Learning and YOLOv8

Abstract: Shoplifting is a major concern for retailers, leading to substantial financial losses worldwide. Traditional surveillance methods rely on manual monitoring ...
IEEE

Robust Distant Small Object Detection Using Radar-Vision Fusion and Prior-Enhanced Query Generation in Autonomous Driving

Abstract: Detecting distant small objects under adverse visual conditions such as rain, fog, or low light remains a critical challenge in autonomous driving. To address this issue, we propose a novel ...
IEEE

A Multi-Scale Attention Transformer for Martian Dust Devil Detection in Remote Sensing Imagery

Abstract: Detecting Martian dust devils remains a challenging task due to the scarcity of high-quality annotated data, significant variations in scale, blurred boundaries, and complex surface textures ...
IEEE

Design of an improved model for real-time fault detection and localization using hybrid transformer-CNN and graph neural networks

Abstract: Accurate real-time fault detection, localization, and classification techniques are necessary to maintain grid stability and prevent faults. Traditional techniques have low accuracy rates, ...
IEEE

Efficient Detection of Objects Near a Robot Manipulator via Miniature Time-of-Flight Sensors

Abstract: We provide a method for detecting and localizing objects near a robot arm using arm-mounted miniature time-of-flight sensors. A key challenge when using arm-mounted sensors is ...
IEEE

TiGDistill-BEV: Multi-view BEV 3D Object Detection via Target Inner-Geometry Learning Distillation

Abstract: Accurate multi-view 3D object detection is essential for applications such as autonomous driving. Researchers have consistently aimed to leverage LiDAR’s precise spatial information to ...
IEEE

Salient Object Detection of Dynamic Night Scenes via Bio-Inspired Spotlight Attention and Hierarchical Edge-Texture Fusion

Abstract: The perception of night scenes is of crucial importance for driving safety. In the dimly lit night environment, as the visibility of objects decreases, both experienced and inexperienced ...
IEEE

CNN vs. Transformer-Based Models for Deepfake Detection: A Comparative Analysis

Abstract: As deepfake technology has rapidly progressed, it has become a concern for media authenticity, cybersecurity, and digital forensics. In this work, we compare and contrast CNNs and ...
IEEE

Enhanced Underwater Object Detection by Tracking in Sonar Images Using Deep Learning and Vehicle Motion Data

Abstract: This paper presents a real-time object detection and tracking algorithm for forward-looking sonar image sequences to enhance navigation and obstacle avoidance algorithms for autonomous ...