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

Secure Spread Spectrum Image Steganography Using a CNN-Based Learned Detector

Abstract: Spread Spectrum Image Steganography (SSIS) represents a promising approach for embedding secret data into a cover image. In conventional methods, a pseudo-noise (PN) sequence functions as a ...
IEEE

Co-Evolutionary Dual-Tree Genetic Programming for Fine-Grained Flower Image Classification

Abstract: Fine-grained flower image classification (FGFIC) is challenging due to high similarities among species and variations within species, especially with limited training data. Existing genetic ...
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 ...
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

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

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

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.
GitHub

Umer-Farooq-CS/CNN-CIFAR10-Classification-GPU-Optimized

This project implements a state-of-the-art CNN architecture for CIFAR-10 image classification, achieving 88.82% accuracy through systematic hyperparameter optimization. The implementation includes GPU ...