IEEE

Transformer-Embedded Attentive CNN for Spectral Image Analysis of Rice Blast Syndromes

Abstract: Leaf blast disease is a significant constraint in world-wide rice production systems, necessitating effective monitoring for optimized crop-yield management. Satellite-derived land-surface ...
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

Domain-Aware Adversarial Domain Augmentation Network for Hyperspectral Image Classification

Abstract: Classifying hyperspectral remote sensing images across different scenes has recently emerged as a significant challenge. When only historical labeled images (source domain, SD) are available ...
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

Hybrid ResNet-ViT Transfer Learning Approach for Brain Stroke Classification on Computed Tomography Images

Abstract: This study investigates the utilization of a hybrid Convolutional Neural Network (CNN) and Vision Transformer (ViT) model, employing transfer learning methods, to enhance brain stroke ...
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

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 ...
IEEE

Optimizing CNN-GRU Hybrid Ratios for Resource-Constrained Audio Classification: A Systematic Study From Parameter Efficiency to MCU Deployment

Abstract: Urban sound classification has become a critical enabling technology for Internet of Things (IoT) applications, smart cities, and environmental monitoring systems. Despite advances in deep ...
IEEE

Enhancing Medical Image Super-Resolution Using CNN and GAN Approaches

Abstract: Improving the resolution of medical images is an important task in ensuring trustworthy diagnosis and effective monitoring of diseases. Of the newest deep learning algorithms, Convolutional ...
IEEE

BAN: A Boundary-Aware Network Based on KAN for Robust Hyperspectral Image Classification Against Adversarial Attacks

Abstract: Deep neural networks (DNNs) have achieved significant advancements in hyperspectral image (HSI) classification, enabling critical applications in environmental monitoring, medical imaging, ...