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

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

Inter-Patient Classification With Encoded Peripheral Pulse Series and Multi-Task Fusion CNN: Application in Type 2 Diabetes

Abstract: Diabetes mellitus, a chronic disease associated with elevated accumulation of glucose in the blood, is generally diagnosed through an invasive blood test such as oral glucose tolerance test ...
IEEE

Plant pathology Perception based on feature Selection GLCM and classification using CNN

Agriculture supports the growth of the economy as it feeds the people and gives them jobs. People working in agriculture must learn to find plant diseases. The most useful way to save crops is to stop ...
IEEE

A Review on Hyper Spectral Image Classification using CNN and Deep Learning Techniques

Abstract: Hyperspectral Imaging (HSI) has undeniably transformed various real-world applications by capturing intricate spectral information at every pixel. Nevertheless, the nonlinear relationships ...
IEEE

Design of an Explainable Deep Learning Framework for ECG-Based Arrhythmia Prediction

Abstract: Arrhythmia refers to abnormal deviations in the normal heart rhythm, possibly signifying severe cardiovascular conditions. The manual identification of arrhythmias by ECG analysis is ...