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

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

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

FRFSL: Feature Reconstruction-Based Cross-Domain Few-Shot Learning for Coastal Wetland Hyperspectral Image Classification

Abstract: Hyperspectral image classification (HSIC) is a valuable method for identifying coastal wetland vegetation, but challenges like environmental complexity and difficulty in distinguishing land ...
IEEE

An Analysis of City Image by Exploiting Social Media: Toward a Deeper Understanding of Multiple Characteristics and Their Temporal Changes Using Machine Learning

Abstract: Since successful city branding plays a crucial role in establishing a city’s competitiveness and uniqueness, cities worldwide are actively involved in shaping their city images. City images ...
IEEE

Hyperparameter Optimization of CNN Models for Plant Leaf Disease Classification Using Optuna

Abstract: Leaf diseases are a major challenge for agricultural productivity, requiring accurate and efficient detection methods. This research presents an effective method for multi-class ...
IEEE

A Hybrid CNN-Transformer Knowledge Transfer Technique for Lightweight Skin Lesion Classification using Dermoscopic Image

Abstract: Using dermoscopic images for the classification of skin lesion is crucial for early skin cancer detection, but resource limitations hinder complex deep learning model applications in ...