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 ...
Edhat

AI Helps Explain How Covert Attention Works And Uncovers New Neuron Types

Shifting focus on a visual scene without moving our eyes — think driving, or reading a room for the reaction to your joke — ...
Janesville Gazette

Takeover bid of parent company means limbo for CNN, some fellow cable networks

Paramount Skydance's hostile takeover bid of Warner Bros. Discovery, announced Monday, places CNN and its sister cable networks squarely back into what is likely to be an extended period of management ...
IEEE

A Multi-Scale Feature Refinement and Dual-Attention Enhanced Dynamic Convolutional Network for Speech-Based Depression and ADHD Assessment

Abstract: In the area of affective computing, speech has been identified as a promising biomarker for assessing depression and attention deficit hyperactivity disorder (ADHD). These disorders manifest ...
Scientific Research Publishing

Zhang, X., Zhao, J. and LeCun, Y. (2015) Character-Level Convolutional Networks for Text Classification.

ABSTRACT: This study presents a comparative analysis of two distinct machine learning approaches for multilingual text identification: character-level neural networks (CNN/RNN) and traditional Naive ...