A synthetic MRI pretraining strategy reduced computing requirements and outperformed ImageNet-based models across a range of ...

The peer-reviewed publication details research from EMVision’s (ASX:EMV) EMView study, which used its emu radiofrequency (RF) brain scanning platform and proprietary deep-learning models to identify ...

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...

Neurodegenerative diseases such as Alzheimer's disease (AD) or frontotemporal lobar degeneration (FTLD) involve specific loss of brain volume, detectable in vivo using T1-weighted MRI scans.

A novel, human-inspired approach to training artificial intelligence (AI) systems to identify objects and navigate their surroundings could set the stage for the development of more advanced AI ...

Abstract: Contrastive self-supervised learning (CSSL) is a promising method for extracting effective features from unlabeled data. It performs well in image-level tasks, such as image classification ...

Action recognition is an important component of human-computer interaction, and multimodal feature representation and learning methods can be used to improve recognition performance due to the ...

Abstract: In remote sensing, numerous unlabeled images are continuously accumulated over time, and it is difficult to annotate all the data. Therefore, a self-supervised learning technique that can ...