A Yann LeCun–Linked Startup Charts a New Path to AGI

As the world’s largest companies pour hundreds of billions of dollars into large language models, San Francisco-based Logical ...
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 ...
IEEE

Evolutionary Neural Architecture Search for Remote Sensing Image Classification

Abstract: Remote sensing scene classification is a vital task in remote sensing image analysis with significant application potential. In recent years, convolutional neural network (CNN)-based methods ...
Frontiers

Image steganalysis using LSTM fused convolutional neural networks for secure telemedicine

Deep learning-based image steganalysis has progressed in recent times, with efforts more concerted toward prioritizing detection accuracy over lightweight frameworks. In the context of AI-driven ...
IEEE

Multiscale Gaussian Process-Driven Graph Convolutional Neural Network for Polarimetric SAR Image Classification

Abstract: By focusing on the structure exploration and information propagation from non-Euclidean data space, graph convolutional neural network (GCN), which can extract abundant and discriminative ...
The New York Times

Trump Seeks to Cut Basic Scientific Research by Roughly One-Third, Report Shows

An analysis by the American Association for the Advancement of Science shows the impact of the administration’s budget plan on the kind of studies that produce the most breakthroughs. By William J.
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, ...
PNAS

The principles behind equivariant neural networks for physics and chemistry

A distinguishing feature of the neural network models used in Physics and Chemistry is that they must obey basic underlying symmetries, such as symmetry to translations, rotations, and the exchange of ...