IEEE

A Novel CNN Architecture for Alzheimer's Disease Classification Using MRI Images: Comparison with Traditional Machine Learning Models

Abstract: Automated medical image processing has significantly improved with recent advances in deep learning and imaging technologies, particularly in the area of neuroimaging-based Alzheimer's ...
IEEE

Enhanced CNN Architecture for Accurate Waste Classification in Smart Cities

Abstract: Waste management is one of the biggest challenges of the present world as the generation of waste has risen tremendously. In this paper we introduce an automated waste classification system ...
IEEE

The pseudo-siamese framework combines Transformer and CNN for medical image generation

Abstract: Multi-phase medical imaging can provide significant improvement in disease multi-modal diagnosis. However, medical image data often suffer from modality missing issues. Therefore, ...
IEEE

Hybrid Attention-Based Residual Network for Image Classification

Abstract: Residual Attention Networks (RANs) are a class of Convolutional Neural Networks (CNNs) that integrate attention mechanisms into deep architectures. RANs employ stacked attention modules to ...
IEEE

An SAGPSO-CNN Approach for Supervised Fault Classification in MVdc Shipboard Power Systems

Abstract: All-electric ships (AESs) utilizing medium-voltage dc (MVdc) shipboard power systems (SPSs) rely on a limited number of generators to supply power to propulsion units and onboard loads. To ...
IEEE

FCTFANet: A Fused CNN-Transformer Feature Aggregator Network for Image Restoration

Abstract: Convolutional neural networks (CNNs) have been foundational in deep learning architectures for image processing, and recently, Transformer networks have emerged, bringing further ...