Deep learning models assemble multiple layers of these artificial neurons into a vast web of evolving connections. And the models juggle data on levels far beyond what the human mind can follow.

Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically ...

More information: Mardava R. Gubbi et al, Deep learning in vivo catheter tip locations for photoacoustic-guided cardiac interventions, Journal of Biomedical Optics (2023). DOI: 10.1117/1.JBO.29.S1 ...

Since RNN uses iterative loops to process the data, it works well for small experiments, but it takes a month if you have one 8 GB GPU to do large machine learning.