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

BAN: A Boundary-Aware Network Based on KAN for Robust Hyperspectral Image Classification Against Adversarial Attacks

Abstract: Deep neural networks (DNNs) have achieved significant advancements in hyperspectral image (HSI) classification, enabling critical applications in environmental monitoring, medical imaging, ...
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

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

Combine Meta-Learning With Feature Alignment for Cross-Domain Heterogeneous Hyperspectral Image Classification

Abstract: The scarcity of labeled samples results in the challenge of small sample size in hyperspectral image (HSI) classification. Transfer learning offers hope for solving this problem. In ...
IEEE

BreNet: Attention-Enhanced Multi-Scale CNN Framework for Breast Cancer Classification in Histopathological Images

Abstract: Breast cancer remains a leading cause of mortality among women worldwide, emphasizing the critical importance of early and accurate detection in improving patient outcomes and treatment ...
IEEE

Brain Cancer MRI Classification using CNN Architectures with Grid Search Enhanced with Coordinate Ascent Optimization

Abstract: Magnetic resonance imaging (MRI) is an important tool for brain cancer diagnosis and classification. Combined with modern convolutional neural network (CNN) technology, it can effectively ...
IEEE

Efficient and Interpretable Otoscopic Image Classification via Distilled CNN With Adaptive Channel Attention

Abstract: Accurate classification of otoscopic ear images is crucial for early diagnosis of ear pathologies such as Chronic Otitis Media, Earwax Plug, and Myringosclerosis. In this study, we propose a ...
Reuters

Freestyle-Skiers aim to project positive US image amid protests

Protests in Italy against U.S. ICE role at Games Skiers express mixed emotions about representing U.S Team aiming to showcase unity and positive American values LIVIGNO, Italy, Feb 6 - American ...
IEEE

Dual-Graph Knowledge Distillation Meets Multiscale CNN: A Novel Ensemble Approach for Few-Shot Hyperspectral Image Classification

Hyperspectral image (HSI) classification aims at categorizing each pixel in an HSI, facilitating precise identification and differentiation of various land cover types. In recent years, graph neural ...