Deep Learning: Current State

Abstract

Deep learning, a derived from machine learning, has grown into widespread usage with applications as diverse as cancer detection, elephant spotting, and game development. The number of published studies shows an increasing interest by researchers because of its demonstrated ability to achieve high performance in the solution of complex problems, the wide availability of data and computing resources, and the groundbreaking development of effective algorithms. This paper reviews the current state of deep learning. It includes the revision of basic concepts, the survey of techniques, the description of an ample array of applications and the discussion of some of its most intriguing open problems.