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

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

Reconstruction-Enhanced Prototype Network for Hyperspectral Image Open-Set Classification

Abstract: With the gradual maturity of deep learning technology and its extensive application in the field of remote sensing, hyperspectral image (HSI) classification technology has made tremendous ...
IEEE

A Fast and Memory-Efficient CNN Accelerator for ECG Classification in Remote Healthcare Systems

Abstract: Electrocardiogram (ECG) classification is crucial for addressing cardiovascular challenges in remote healthcare systems. Recent advances in artificial intelligence, particularly ...
IEEE

Bone Fracture Classification Using Deep Learning Models with Transfer Learning

Abstract: Bone fracture can be defined as the complete or partial disruption of the integrity of bone tissue. Early and accurate diagnosis of fractures plays a decisive role in the effectiveness of ...
IEEE

Remote Sensing Scene Image Classification with Swin Transformer-Based Transfer Learning

Abstract: In remote sensing classification problems, high visual similarity between scenes reduces the classification performance of traditional methods. Therefore, advanced deep neural network models ...
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

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 ...