Titlebook: Handbook of Deep Learning Applications; Valentina Emilia Balas,Sanjiban Sekhar Roy,Pijush Book 2019 Springer Nature Switzerland AG 2019 D

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Sanghamitra Bandyopadhyay,Sriparna Sahaarning has become an efficient solution for learning in the context of supervisioned learning. Deep Learning [.] consists in using Artificial Neural Networks (ANN or NN) with several hidden layers, typically also with a large number of nodes in each layer.

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Personally Sound: Tapping into Your Talentsn. Automation has offered promised returns of improvements in safety, productivity and reduced costs. Many industry leaders are specifically working on the application of autonomous technology in transportation to produce “driverless” or fully autonomous vehicles. A key technology that has the poten

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Ein ?u?erst kaprizi?ses Gegenüberarameters. Precise and satisfactory document representation is the key to supporting computer models in accessing the underlying meaning in written language. Automated text classification, where the objective is to assign a set of categories to documents, is a classic problem. The range of studies i

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https://doi.org/10.1007/978-3-322-91685-3 In particular, convolutional neural network has shown better capabilities to segment and/or classify medical images like ultrasound and CT scan images in comparison to previously used conventional machine learning techniques. This chapter includes applications of deep learning techniques in two dif

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Ein Wort zu Gattung und Schreibweise,application area in the computer vision community. However, with the developments of deep learning, there has been an increasing interest about this topic. In this chapter, we present a comprehensive review of the computer vision techniques for marine species recognition, mainly from the perspective