This study presents a valuable application of a video-text alignment deep neural network model to improve neural encoding of naturalistic stimuli in fMRI. The authors found that models based on ...

The integration of deep learning in biodiesel research accelerates feedstock evaluation and optimizes production, making it ...

The deep learning pioneers believe that better neural network architectures will eventually lead to all aspects of human and animal intelligence, including symbol manipulation, reasoning, causal ...

Neural networks are now applied across the spectrum of AI applications while deep learning is reserved for more specialized or advanced AI use cases.

Born in the 1950s, the concept of an artificial neural network has progressed considerably. Today, known as “deep learning”, its uses have expanded to many areas, including finance.

It's a novel idea, using light diffracted through numerous plates instead of electrons. And to some, it might seem a little like replacing a computer with an abacus, but researchers at UCLA have ...

Artificial Neural Networks: Learning by Doing Designed to mimic the brain itself, artificial neural networks use mathematical equations to identify and predict patterns in datasets and images.

Deep learning has advanced rapidly, driving breakthroughs in image recognition, natural language processing, and autonomous ...