IEEE

Global–Local Residual Fusion Network for Hyperspectral Image Classification

Abstract: As hyperspectral images (HSIs) continue to increase in data resolution and information richness, current deep learning models need to enhance their feature extraction and understanding ...
IEEE

A Lightweight Spatial–Spectral Deformable CNN for UAV Hyperspectral Image Classification

Abstract: In recent years, uncrewed aerial vehicle (UAV) technology has shown great potential for application in hyperspectral image (HSI) classification tasks due to its advantages of flexible ...
IEEE

Classification of Eye Diseases Using CNN on Fundus Images

Abstract: Eye diseases represent a critical global health concern, affecting approximately 2.2 billion individuals with visual impairments or blindness and underscoring the urgent need for accessible ...
IEEE

Water Quality Assessment Leveraging CNN-LSTM and Gradient Boosting for Prediction and Classification

Abstract: Accurate prediction of water quality can support in water resource management by the early warning of water pollution. Water quality assessment is crucial for ensuring the availability of ...
IEEE

Transformer-Driven Active Transfer Learning for Cross-Hyperspectral Image Classification

Abstract: Hyperspectral image (HSI) classification presents inherent challenges due to high spectral dimensionality, significant domain shifts, and limited availability of labeled data. To address ...
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

Histopathological Image Processing for Lung Carcinoma Classification: A Comparative Study of Stain Normalization Methods for CNN-Based Analysis

Abstract: In the present era, Cancer-related deaths are predominantly driven by lung cancer globally, causing significant deaths across all demographics. Precise prediction and evaluation of treatment ...
IEEE

Hybrid CNN-ViT Model for Intracranial Hemorrhage Detection and Classification in DICOM Images

Abstract: Intracranial hemorrhage (ICH) refers to bleeding within the brain, a global concern that underscores the im-portance of early detection. ICH is typically detected using computed tomography ...
IEEE

Evaluating Lightweight CNN Models with CBAM for Explainable AI Skin Cancer Classification using GradCAM and ScoreCAM

Abstract: Skin cancer continues to be a prevalent and deadly malignancies cancer globally, necessitating early and accurate diagnosis. Lightweight CNN has emerged as effective tools for automated skin ...
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

Fully Perturbed Self-Ensemble Framework using Cascaded Parallel CNN-Transformer for Semi-Supervised Medical Image Segmentation

Abstract: Semi-supervised learning (SSL) has achieved remarkable progress in the field of medical image segmentation (MIS), but it still faces two main challenges. First, the consistency learning ...
IEEE

Enhancing Alcohol Use Disorder Diagnosis Using EEG and Hybrid CNN–BiLSTM Deep Learning Models

Abstract: Alcohol misuse remains a major global health concern, contributing to approximately 3.3 million deaths each year. Conventional methods for diagnosing Alcohol Use Disorder (AUD), such as self ...