Abstract: The trend of integrating different distributed generation sources into the existing grid have increased the probability of power quality disturbances to a threatening level. Eventually, ...

Object detection in remote sensing imagery plays a vital role across various fields, including industrial monitoring, agricultural assessment, and military surveillance (D’Acremont et al., 2019) 1.

This repo contains all my Deep Learning semester work, including implementations of FNNs, CNNs, autoencoders, CBOW, and transfer learning. I explored TensorFlow, Keras, PyTorch, and Theano while ...

In this study, we propose a CNN-GAN-based real-time processing technique for filtering images of underwater cables used in power systems. This addresses the excessive interference impurities that are ...

Abstract: If diabetic retinopathy is not identified and treated right away, it is a dangerous side effect of diabetes that will cause blindness. In this work, we investigate novel deep learning (DL) ...

This research introduces an innovative approach to image classification, by making use of Vision Transformer (ViT) architecture. In fact, Vision Transformers (ViT) have emerged as a promising option ...

A whistle stop tour of how to use the latest image classification techniques to build and understand a deep neural network bird classifier This is an investigation using PyTorch CNNs of deep image ...

This study aimed to develop a bimodal convolutional neural network (CNN) by co-training grayscale images and scalograms of ECG for cardiovascular disease classification. The bimodal CNN model was ...

The constantly evolving human–machine interaction and advancement in sociotechnical systems have made it essential to analyze vital human factors such as mental workload, vigilance, fatigue, and ...