Frontiers

Neural Network Dynamics: Unraveling Spiking and Synaptic Plasticity in Learning and Memory

Neuroscience continually strives to unravel the intricate relationship between neural network morphology, spiking dynamics, and their resulting functional ...
IEEE

Physics-Informed Neural Network for Model Prediction and Dynamics Parameter Identification of Collaborative Robot Joints

Abstract: Collaborative robots have promising potential for widespread use in small-and-medium-sized enterprise (SME) manufacturing and production due to the development of increasingly sophisticated ...
Open Heart

Development and validation of a deep learning model for severe mitral stenosis detection from chest X-rays

Background Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains ...
AlphaGalileo

Physics-Informed AI for Subsurface Modeling: Bridging Emulsion Flooding and Carbon Storage

Omarkhan Samarkanov, Masoud Riazi School of Mining and Geosciences Presented at: 6th EAGE Global Energy Transition Conference & Exhibition (GET ...
Scientific Research Publishing

Organoid Intelligence: Bridging the Gap Between Biological and Artificial Neural Networks ()

Organoid Intelligence (OI) represents a groundbreaking convergence of biology and technology, aiming to redefine biocomputing using brain organoids—three-dimensional neural structures derived from ...
AlphaGalileo

Space Computing Power Networks: A New Frontier for Satellite Technologies

Discover the future of satellite technology with space computing power networks (Space-CPN). This innovative architecture ...
IEEE

C-DNN: An Energy-Efficient Complementary Deep-Neural-Network Processor With Heterogeneous CNN/SNN Core Architecture

Abstract: In this article, we propose a complementary deep-neural-network (C-DNN) processor by combining convolutional neural network (CNN) and spiking neural network (SNN) to take advantage of them.