Deep learning works by using multilayered neural networks. To make sense of the data they are fed, such as photos, neural ...

Understanding Deep Learning. To understand deep learning and how it differs from machine learning, you need to understand ...

Deep learning (DL) is based on extracting sophisticated ... Initially, machine learning developers prioritized model performance and application efficacy over clarifying the model’s decision ...

This deep learning-based approach provides an entirely new framework to conduct holographic imaging by rapidly eliminating twin-image and self-interference-related spatial artifacts. This neural ...

The study, "3D Convolutional Deep Learning for Nonlinear Estimation ... in advancing the understanding of human metabolism and the application of new technologies such as 3D optical imaging ...

The artificial intelligence (AI) machine AlphaGo astounded the world by beating world go champion Lee Se-dol in the first ...

Noise in confocal images is overwhelmingly a result of shot noise; this makes confocal images an ideal target for deep learning,as the source of noise is essentially constrained to one source.