IEEE

Hybrid CNN-Transformer Model for Accurate Classification of Human Attention Levels Using Workplace EEG Data

Abstract: Accurately detecting human attention levels is a key challenge in cognitive neuroscience, with broad application value in improving productivity. Although Electroencephalography (EEG) ...
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

UAV Image Classification: A Comparative Evaluation of CNN Models

Abstract: Aerial image classification plays a vital role in applications such as building footprint extraction, water/soil analysis, 3D reconstruction. Accurate classification enables timely ...
IEEE

Explainable Brain Tumor Classification using CNN and GradCAM

Abstract: One of the most critical neurological conditions is Brain tumors, timely and correct diagnosis is needed for effective treatment. Advances in neuroimaging technology such as MRI, limitations ...
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

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 ...
IEEE

Water Quality Assessment Leveraging CNN-LSTM and Gradient Boosting for Prediction and Classification

Abstract: Accurate prediction of water quality can support in water resource management by the early warning of water pollution. Water quality assessment is crucial for ensuring the availability of ...
IEEE

Land Use Classification of High-Resolution Remote Sensing Imagery Incorporating Global-Local Interactive Features Across Optical Domain and Land Cover Primitives

Abstract: The Land Use (LU) classification of remote sensing (RS) images has broad applications in various fields. In recent years, hybrid CNN-Transformer models have been widely applied to the LU ...
IEEE

LPP-CNN: A Lightweight Privacy-Preserving Object Classification Framework for Military Vehicle Images

Abstract: In this article, we propose a lightweight privacy-preserving convolutional neural network (LPP-CNN) framework for military vehicle image classification. Existing target classification ...
IEEE

Hybrid CNN-ViT Model for Intracranial Hemorrhage Detection and Classification in DICOM Images

Abstract: Intracranial hemorrhage (ICH) refers to bleeding within the brain, a global concern that underscores the im-portance of early detection. ICH is typically detected using computed tomography ...
IEEE

Evaluating Lightweight CNN Models with CBAM for Explainable AI Skin Cancer Classification using GradCAM and ScoreCAM

Abstract: Skin cancer continues to be a prevalent and deadly malignancies cancer globally, necessitating early and accurate diagnosis. Lightweight CNN has emerged as effective tools for automated skin ...
IEEE

Fully Perturbed Self-Ensemble Framework using Cascaded Parallel CNN-Transformer for Semi-Supervised Medical Image Segmentation

Abstract: Semi-supervised learning (SSL) has achieved remarkable progress in the field of medical image segmentation (MIS), but it still faces two main challenges. First, the consistency learning ...