Pedrycz - Deep Learning: Algorithms and Applications (Studies in Computational Intelligence, 865)

The series Studies in Computational Intelligence (SCI) publishes new developments and advances in the various areas of computational intelligencequickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life sciences, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution, which enable both wide and rapid dissemination of research output.

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Deep learning has entered a period of designing, implementing, and deploying intensive and diverse applications, which are now visible in numerous areas. Successful case studies became a consequence of the prudent, carefully drafted fundamental concept that transformed ways in such real-world problems are perceived, formalized, and solved at the increased level of machine-centered and automatic fashion. Central to all pursuits are algorithms that help realize the principles of deep learning in an efficient way. Algorithms deliver a sound alignment with the specificity of the applied nature of the practical problem by addressing the computing requirements and selecting/adjusting overall algorithmic settings.

The volume is composed of 11 chapters and reflects the wealth of algorithms of deep learning and their application studies in the plethora of areas including imaging, seismic tomography, power series forecasting, smart grids, surveillance, security, health care, environmental engineering, and marine sciences.

We would like to express our thanks to the Series Editor, Prof. Janusz Kacprzyk. He has always been enthusiastic and highly supportive of this project. We are indebted to the professionals at Springer; the team has made the overall production process highly efficient and completed in a timely manner.