IEEE

3D CT Liver Images Lesion Extraction and Classification for Using 3D-CNN with GLRLM

Abstract: The imaging technique known as computed tomography (CT) is often considered to be the most reliable way for non-invasive diagnosis. Through the use of three-dimensional (3D) computed ...
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

SeCoMIL: Semantic Anchor-based Context-Aware Multiple Instance Learning for Whole Slide Image Classification

Abstract: Context-aware Multiple Instance Learning (MIL) is gaining popularity in Whole Slide Image (WSI) classification. Existing methods typically convert instances in a WSI into one-dimensional ...
IEEE

HZSCM: Hyperspectral Image Zero-Shot Classification via Vision-Language Models

Abstract: Most hyperspectral image (HSI) classification methods assume that all classes in the test set are present during training. However, in real-world applications, acquiring labeled training ...
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

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

DBMLLA: Double-Branch Mamba-Like Linear Attention Network for Hyperspectral Image Classification

Abstract: Convolutional neural networks (CNNs) and transformers have made remarkable achievements in hyperspectral image classification (HSIC). Unfortunately, CNN-based methods struggle to capture the ...
IEEE

S2DBFT: Spectral–Spatial Dual-Branch Fusion Transformer for Hyperspectral Image Classification

Abstract: Convolutional neural network (CNN)- and Transformer-based models have achieved remarkable success in hyperspectral image (HSI) classification tasks due to their outstanding ability to ...
CNET

If You Want Better AI Images, You Need to Use These Key Ingredients in Your Prompt

Writing a prompt to create an AI image isn't hard but you need to know the right things to include. Katelyn is a writer with CNET covering artificial intelligence, including chatbots, image and video ...
IEEE

Open-Set Domain Adaptation for Hyperspectral Image Classification Based on Reconstruction Discrepancy and Feature Alignment

Abstract: For hyperspectral image classification, domain adaptation algorithms often assume that the source domain and target domain share the same label space, and thus, classify all samples in the ...
MLive

Trump is now embracing Project 2025, using federal shutdown to pursue its goals

NEW YORK (AP) — President Donald Trump is openly embracing the conservative blueprint he desperately tried to distance himself from during the 2024 campaign, as one of its architects works to use the ...