eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
IEEE

Efficient Group Cosine Convolutional Neural Network for EEG-Based Seizure Identification

Abstract: Epilepsy is a common neurological disease, and its diagnosis usually depends on labor-intensive visual inspection of electroencephalogram (EEG). Although various deep learning-based seizure ...
News-Medical.Net

AI uncovers hidden mechanisms of covert attention and emergent neuron types

Shifting focus on a visual scene without moving our eyes - think driving, or reading a room for the reaction to your joke - ...
EurekAlert!

A new paradigm in spectroscopic sensing: The revolutionary leap of SERS-optical waveguide integration and ai-enabled ultra-sensitive detection

Recently, a collaborative team from multiple institutions, including CIOMP, published a review article in Light: Science & ...
IEEE

A Quantum Spatial Graph Convolutional Neural Network Model on Quantum Circuits

Abstract: This article proposes a quantum spatial graph convolutional neural network (QSGCN) model that is implementable on quantum circuits, providing a novel avenue to processing non-Euclidean type ...
GitHub

Deep neural networks

Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural ...