IEEE

Enhancing CNN-Based Motion Sickness Detection using EEG Signals Weighted by Motion Sickness Dose Value

Abstract: With the advancement of autonomous driving technologies, passengers increasingly engage in non-driving activities. However, these activities are often limited by motion sickness (MS), which ...
IEEE

Multilevel Multimodal CNN–Transformer Fusion Network for Land Use and Land Cover Classification

Abstract: In remote sensing (RS), convolutional neural networks (CNNs) are well-recognized for their spatial–spectral feature extraction capabilities, whereas vision transformers (ViTs), which ...
IEEE

Image-Based Skin Disease Detection using Convolutional Neural Networks

Abstract: As skin diseases continue to emerge worldwide, there is a growing need for fast and accurate diagnosis. However, access to dermatologists remains limited, especially in remote and ...
IEEE

KDLight: A Lightweight Knowledge Distillation Framework for Medical Image Classification

Abstract: Conventional standalone approaches for diagnosing individual diseases often fail to achieve robust generalization because they are severely impacted by overfitting. This results in poor ...
IEEE

Automated Deep Learning System for Early Detection of Stroke Using CNN Architecture

Abstract: Strokes are a major cause of disability worldwide, with ischemic and hemorrhagic strokes accounting for the majority of cases. In India, stroke remains the second most common cause of ...
IEEE

Language-Guided and Similarity-Aware Network for Few-Shot Classification of Coastal Wetland Hyperspectral Images

Abstract: In recent years, few-shot learning (FSL) has made significant progress in hyperspectral image classification (HSIC) by transferring meta-knowledge from a source domain with sufficient ...
IEEE

Improved Transformer Network Based on Multiscale Grouping Feature Fusion for Hyperspectral Image Classification

Abstract: In recent years, hyperspectral image classification methods based on convolutional neural networks and Transformer architectures have achieved remarkable success. However, existing ...
IEEE

SemiBaCon: Semi-Supervised Balanced Contrastive Learning for Multimodal Remote Sensing Image Classification

Abstract: The limited availability of annotated training data significantly constrains the classification accuracy of hyperspectral image (HSI) and LiDAR fusion approaches. Although contrastive ...
IEEE

AI-based Circuit Fault Detection and Classification using Python Simulation

Abstract: Electrical circuits play a vital role in industrial, automotive, and power systems, where even minor faults can lead to severe performance degradation or system failure. Traditional fault ...
IEEE

Cross-Domain Hyperspectral Image Classification via Mamba–CNN and Knowledge Distillation

Abstract: Domain adaptation (DA)-based cross-domain hyperspectral image (HSI) classification methods have garnered significant attention. The majority of DA techniques utilize models based on ...
IEEE

Semantic-Guided Cross-Modal Feature Alignment for Cross-Domain Few-Shot Hyperspectral Image Classification

Abstract: When facing the challenge of limited samples, existing hyperspectral image (HSI) classification methods typically assume that source domain samples (with prior knowledge) and target task ...
IEEE

Improving Robustness and Reliability in Medical Image Classification With Latent-Guided Diffusion and Nested-Ensembles

Abstract: Once deployed, medical image analysis methods are often faced with unexpected image corruptions and noise perturbations. These unknown covariate shifts present significant challenges to deep ...