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

A Heterogeneous CNN with Transformers for Image Denoising

Abstract: Deep learning models often emphasize structural information over long-range dependencies when producing cleaner images. To enhance the robustness of the resulting denoisers, this work ...
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

A CNN network for coronary chronic total occlusion state classification using image data

Abstract: Chronic total occlusion (CTO) is a critical determinant of treatment efficacy in coronary artery disease, but its accurate diagnosis remains heavily reliant on the expertise of experienced ...
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

Optimizing Hybrid Classification Using 1D-CNN and LSTM for EEG-Based Emotion Recognition

Abstract: This research aims to enhance the ability of computers to classify emotional states from brain signals using EEG data. Emotions are complex mental states that can significantly affect a ...
KOAM News Now

Latin Grammy winner Bobby Pulido will win Democratic primary for Texas’ 15th District, CNN projects

Pharr, Texas (CNN) — Tejano singer Bobby Pulido will win the Democratic primary for Texas’ 15th Congressional District, CNN projects, defeating emergency room physician Ada Cuellar. Pulido will face ...