IEEE

Language-Guided and Similarity-Aware Network for Few-Shot Classification of Coastal Wetland Hyperspectral Images

Abstract: In recent years, few-shot learning (FSL) has made significant progress in hyperspectral image classification (HSIC) by transferring meta-knowledge from a source domain with sufficient ...
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

Explaining Fine-Grained Image Classification Using Evolutionary Search and the Stable Diffusion Model

Abstract: Deep learning models have shown impressive performance across a range of computer vision tasks. However, their lack of transparency limits their adoption in tasks where a clear understanding ...
CNN

After ‘digital undressing’ criticism, Elon Musk’s Grok limits some image generation to paid subscribers

Elon Musk’s Grok chatbot has limited some of its Imagine image generation features to paid X subscribers, days after international uproar over the AI tool responded to user requests by “digitally ...
IEEE

Matching Street View Images for the Classification of Urban Land Use From Very-High-Resolution Remote Sensing Images

Abstract: Street view (SV) images provide valuable supplementary data for characterizing the functional attributes of land use types, improving urban land use classification based on ...
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

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

BinaryViT: Binary Vision Transformer for Hyperspectral Image Classification

Abstract: Vision transformers have demonstrated remarkable performance in hyperspectral image classification tasks. However, their complex computational mechanisms and excessive parameterization ...
IEEE

Hyperspectral Image Classification Using Gated Adaptable Convolutional-Based Kolmogorov–Arnold Network

Abstract: Vision transformers (ViTs) and convolutional neural networks (CNNs) have demonstrated remarkable performance in classifying complicated hyperspectral images (HSIs). However, these models ...
IEEE

Robust Image Steganography Approach Based on Edge Detection Combined With CNN Algorithm

Abstract: Image steganography conceals secret data within a cover image to generate a new image (stego image) in a manner that makes the secret data undetectable. The main problem in image ...
IEEE

Self-Supervised Mamba for Hyperspectral Image Classification

Abstract: Recent advances in Mamba-based architectures have demonstrated promising potential for hyperspectral image classification (HSIC), offering linear-complexity long-range dependency modeling.