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

Novel Mask R-CNN Based Mushroom Cluster Tracking in Time-Lapse Images From a Farm Environment

Abstract: This study aims to develop a novel deep learningbased approach to support the automated mushroom growth monitoring using an object tracking algorithm in conjunction with instance ...
IEEE

Semantic-Guided Cross-Modal Feature Alignment for Cross-Domain Few-Shot Hyperspectral Image Classification

Abstract: When facing the challenge of limited samples, existing hyperspectral image (HSI) classification methods typically assume that source domain samples (with prior knowledge) and target task ...
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

Progressive Cluster-Guided Knowledge Distillation for Remote Sensing Image Scene Classification

Abstract: Knowledge distillation (KD) has recently demonstrated remarkable potential in developing lightweight convolutional neural networks for remote sensing image (RSI) scene classification tasks.
IEEE

Image Classification using Quantum Convolutional Neural Network (QCNN)

Abstract: Convolutional Neural Networks (CNNs) are extensively utilized for image classification due to their ability to exploit data correlations effectively. However, traditional CNNs encounter ...
IEEE

An Ensemble Deep Learning Model Using CNN, LSTM and Autoencoder for EEG-Based Parkinson’s Disease Classification

Abstract: Parkinson's disease is a neurological disorder hat effects the movements including shaking, stiffness, difficulty while walking and speaking. This condition will occur when the nerve cells ...
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

Implementation of Brain Tumor Detection and Classification Model Using CNN Approach

Abstract: Unless diagnosed and treated early, brain tumors unusual growths may prove to be lethal. Even with the standard methods, such as MRI scans, to precisely diagnose brain cancers, it may be ...
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

Data Augmentation: Synthetic Image Generation for Medical Images Using Vector Quantized Variational Autoencoders

Abstract: Artificial intelligence (AI) has revolutionized medical imaging, significantly improving diagnostic accuracy via the evaluation of X-rays, MRIs, and CT scans. However, the effectiveness of ...
IEEE

Classification of Eye Diseases Using CNN on Fundus Images

Abstract: Eye diseases represent a critical global health concern, affecting approximately 2.2 billion individuals with visual impairments or blindness and underscoring the urgent need for accessible ...