Researchers at KAUST have proposed a 'super transformer' AI architecture designed to integrate diverse biological data types—such as DNA sequences, gene activity, and tissue images—into a single model ...

Modern biology is awash in data. Scientists can sequence DNA, track gene activity cell-by-cell, map proteins in space, and ...

Depletion of histone H3K27 demethylase exerts anti-tumor activity as a monotherapy and in combination therapy with ceralasertib in non-small cell lung carcinoma. This is an ASCO Meeting Abstract from ...

In the last decade, convolutional neural networks (CNNs) have been the go-to architecture in computer vision, owing to their powerful capability in learning representations from images/videos.

Vision transformers (ViTs) are powerful artificial intelligence (AI) technologies that can identify or categorize objects in images -- however, there are significant challenges related to both ...

A new method for automated concrete bridge damage detection using an efficient Vision Transformer-enhanced anchor-free YOLO (You Only Look Once) has been proposed by researchers from the University of ...

Transformers, first proposed in a Google research paper in 2017, were initially designed for natural language processing (NLP) tasks. Recently, researchers applied transformers to vision applications ...

The object detection required for machine vision applications such as autonomous driving, smart manufacturing, and surveillance applications depends on AI modeling. The goal now is to improve the ...

Computer vision continues to be one of the most dynamic and impactful fields in artificial intelligence. Thanks to breakthroughs in deep learning, architecture design and data efficiency, machines are ...

Artificial intelligence researchers from Meta Platforms Inc. say they’re making progress on the vision of its Chief AI Scientist Yann LeCun to develop a new architecture for machines that can learn ...