Go over the details about Convolutional Neural Nets, explaining their inner meachanisms and the reason why they perform better than fully connected networks. Set up a deep learning dedicated ...

Abstract: In this study, we perform land use classification (LUC) using sequences of multispectral Sentinel-2 images taken over multiple years. It evaluates the convolutional neural network (CNN) ...

In machine learning, Convolutional Neural Networks (CNN or ConvNet) are complex feed forward neural networks. CNNs are used for image classification and recognition because of its high accuracy. It ...

In this work, a novel Hybrid 1-D Convolutional Transformer Neural Network is utilized for diagnosing faults in a Cascaded H-Bridge PMSM drive system. This innovative method exhibits high precision in ...

Exploiting invariances in data is crucial for neural networks to learn efficient representations and to make accurate predictions. Translation invariance is a key symmetry in image processing and lies ...