IEEE

Deep Learning for Radar-Based Target Classification

Abstract: This study explores the application of deep learning techniques for classifying targets such as people, drones, and cars using micro-Doppler radar signals. Micro-Doppler radar excels in ...
IEEE

Hybrid CNN-LSTM Framework for Accurate Detection and Classification of Epileptic Seizures using EEG Signals

Abstract: This work introduces a robust hybrid CNN-LSTM framework designed for the reliable identification and categorization of epileptic seizures using electroencephalogram (EEG) signals. The model ...
IEEE

Air Target Classification Using High-Resolution Range Profiles and Deep/Machine Learning Techniques

Abstract: High-resolution range profiles (HRRPs) offer detailed structural information about air targets, making them crucial for classification and identification in both military and civilian ...
IEEE

SAR Target Classification Enhancement via Synthetic Defocused Image Augmentation Using Kinematic Motion Modeling

Abstract: Deep neural networks (DNNs) have demonstrated remarkable potential in automatic target classification using synthetic aperture radar (SAR) imagery. However, their performance heavily relies ...
IEEE

A Multiple Backbone Feature Fusion Ensemble CNN for Brain Tumor Detection and Classification from MRI Images

Abstract: Accurate classification of brain tumors from magnetic resonance imaging (MRI) scans is essential for early diagnosis and reliable clinical decision-making. However, variations in tumor ...
IEEE

Physics-Aware Deep Fusion Framework and Benchmark for SAR Target Classification

Abstract: The distinctive electromagnetic scattering characteristics of SAR target images are crucial for SAR target recognition. However, existing purely data-driven paradigms often overlook inherent ...
IEEE

Low-Resolution Radar Target Classification Using Vision Transformer Based on Micro-Doppler Signatures

Abstract: Micro-Doppler signatures (m-DSs) have been widely employed for the automatic recognition of various radar targets that exhibit micromotions via time–frequency distributions (TFDs). However, ...
IEEE

Region-Relation Enhanced GNN-CNN for Image Classification

Abstract: Convolutional Neural Networks (CNNs) excel in local feature extraction but struggle to model regional semantic correlations and global context. This paper proposes a GNNintegrated framework ...
IEEE

Research on Ship Target Classification Based on Deep Convolutional Neural Networks

Abstract: With the continuous improvement of intelligent shipping and maritime supervision needs, vision-based ship target classification has become a key technology to enhance maritime situational ...