The AttendSeg deep learning model performs semantic segmentation at an accuracy that is almost on-par with RefineNet while cutting down the number of parameters to 1.19 million.

Please use one of the following formats to cite this article in your essay, paper or report: APA. Cuffari, Benedette. (2025, April 07). Using Deep Learning for Brain Imaging Data Analysis.

Oceans are facing a multitude of climate-induced stresses including acidification, sea-level rise, warming waters, and ice ...

Discover how to build an automated intent classification model by leveraging pre-training data using a BERT encoder, BigQuery, and Google Data Studio.

A research team has developed a diagnostic system that uses artificial intelligence (AI) to accurately identify the type of facial pigmented lesions and support laser treatment decisions. A paper on ...

Liver cancer is the sixth most common cancer globally and a leading cause of cancer-related deaths. Accurate segmentation of liver tumors is a crucial step for the management of the disease, but ...

An AI system called iSeg is reshaping radiation oncology by automatically outlining lung tumors in 3D as they shift with each ...

CONTAIN™ represents the next breakthrough in AI-powered ore sorting from TOMRA Mining – a deep learning solution purpose-built to classify complex inclusion-type ores with unprecedented accuracy. By ...