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

Enhancing GNSS Localization in Urban Canyons With a Hybrid CNN-Autoencoder Approach to LOS/NLOS Classification

Abstract: Non-Line-of-Sight (NLOS) reception is acknowledged as a primary source of positioning error in Global Navigation Satellite System (GNSS) applications ...
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 ...