A witty personal essay on brainrot detox, self-help apps, philosophy, procrastination, and finding sanity in a doomscrolling ...

Using machine learning to guide microscopes could reveal greater insights into the brain's connectome and deepen our ...

The efficacy of deep residual networks is fundamentally predicated on the identity shortcut connection. While this mechanism effectively mitigates the vanishing gradient problem, it imposes a strictly ...

A new machine learning model developed by The George Institute for Global Health can successfully predict heart disease risk in women by analyzing mammograms. The findings were published today in ...

Abstract: The success of deep learning (DL) is often achieved at the expense of large model sizes and high computational complexity during both training and post-training inferences, making it ...

Explore the controversial telescope design that even its maker questioned. We break down the spot diagram to uncover the optics behind the criticism and what it means for your viewing experience.

Purpose: To develop and evaluate deep learning (DL) models for detecting multiple retinal diseases using bimodal imaging of color fundus photography (CFP) and optical coherence tomography (OCT), ...

1 Eye Hospital, The First Affiliated Hospital of Harbin Medical University, Harbin, China 2 School of Intelligent Science and Engineering, Harbin Engineering University, Harbin, China Background: As a ...