This study presents a deep learning model—a type of machine learning that does not require human inputs—to analyze complex clinical and financial data for population risk stratification.

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

Machine-learning algorithms are responsible for the vast majority of the artificial intelligence advancements and applications you hear about. (For more background, check out our first flowchart ...

To overcome this limitation, researchers from Korea led by Professor Jung Eok Son from Seoul National University have created a novel deep-learning based crop model known as "DeepCrop", for ...

A new technical paper titled “A Universal AI-Powered Segmentation Model for PCBA and Semiconductor” was published by researchers at Nordson Corporation. “This paper introduces a novel universal deep ...

Artificial intelligence is playing an increasingly vital role in modern medicine, particularly in interpreting medical images ...

Learn More. Deep learning is a subset of machine learning that uses neural networks with multiple layers to model complicated patterns and representations in data. It excels at tasks like image ...

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. Interestingly ...

Over the past two decades, the biggest evolution of Artificial Intelligence has been the maturation of deep learning as ... the most challenging machine learning model development.