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

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

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

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 ...
IEEE

Mitosis Detection in Breast Histopathology Images Using a Self-Attention-Enhanced Faster R-CNN Framework

Abstract: At present, mitosis detection in breast histopathology images is a critical issue for breast cancer grading. Due to the breast tissue having a complex structure, and mitosis and non-mitosis ...
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 ...
inforum

Port: Attorney General's office asserts F5 Project loans are illegal

MINOT — Attorney General Drew Wrigley's office has notified the F5 Project that the nonprofit may have been raising funds illegally due to an expired registration with the state. A Jan. 6, 2026, ...