EurekAlert!

Chongqing Medical University team: dual-branch graph attention network enables personalized prediction of ECT efficacy in adolescent depression

Major Depressive Disorder (MDD) is a leading cause of disability among adolescents, yet the efficacy of Electroconvulsive ...
Beebom

What is CNN in Deep Learning? The AI Behind Computer Vision

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...
GitHub

ResNet-50 Image Classification

This project implements ResNet-50, a deep convolutional neural network with 50 layers that uses residual connections to enable training of very deep networks. The architecture includes identity ...
Frontiers

Automated classification of midpalatal suture maturation using 2D convolutional neural networks on CBCT scans

School of Dentistry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada Introduction: Accurate assessment of midpalatal suture (MPS) maturation is critical in orthodontics, ...
Frontiers

Comparative analysis of convolutional neural networks and transformer architectures for breast cancer histopathological image classification

The First Hospital of Hunan University of Chinese Medicine, Hunan University of Chinese Medicine, Changsha, China Background: Breast cancer remains the most prevalent malignancy in women globally, ...
IEEE

Learning laws for deep convolutional neural networks with guaranteed convergence

Abstract: Convolutional Neural Networks (CNNs) have shown remarkable success across numerous tasks such as image classification, yet the theoretical understanding of their convergence remains ...
Scientific Research Publishing

Krizhevsky, A., Sutskever, I. and Hinton, G.E. (2012) ImageNet Classification with Deep Convolutional Neural Networks. In: Advances in Neural Information Processing Systems ...

ABSTRACT: The research article studies the impact of data augmentation, particularly 60˚ rotation, on the performance of a ResNet convolutional neural network (CNN) for brain tumor detection using MRI ...
IEEE

Using Deep Convolutional Neural Networks for Earthquake and Explosion Classification

Abstract: Accurate classification of seismic events is essential to prevent confusion in catalogs, which can distort seismic statistics and hazard analyses. Monitoring small-scale explosions aids in ...
Scientific Research Publishing

Krizhevsky, A., Sutskever, I. and Hinton, G.E. (2017) Imagenet Classification with Deep Convolutional Neural Networks. Communications of the ACM, 60, 84-90.

ABSTRACT: Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image data during the past several years. However, they are ...
Ars Technica

You can now download the source code that sparked the AI boom

On Thursday, Google and the Computer History Museum (CHM) jointly released the source code for AlexNet, the convolutional neural network (CNN) that many credit with transforming the AI field in 2012 ...