Deep learning classifier based on NPCA and orthogonal feature selection

Jankowski, S.; Szymański, Z; Dziomin, Uladzimir; Golovko, Vladimir; Barcz, Aleksy

doi:10.1117/12.2249848

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2018

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“…According to the scientists of the Massachusetts Institute of Technology, deep neural networks are on the list of the 10 most promising high technologies capable in the near future to largely transform the everyday life of most people on our planet and solve many problems of artificial intelligence, for example, speech recognition, computer vision, natural language processing, data visualization, etc. [9][10][11][12][13]26].…”

Section: Introductionmentioning

confidence: 99%

Deep Neural Network for Image Recognition Based on the Caffe Framework

Komar

Yakobchuk

Golovko

et al. 2018

2018 IEEE Second International Conference on Data Stream Mining &Amp; Processing (DSMP)

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Deep Leaning of the Neural Networks has become one of the most demanded areas of Information Technology and it has been successfully applied to solving many issues of Artificial Intelligence, for example, speech recognition, computer vision, natural language processing, data visualization. This paper describes the developing the deep neural network model for image recognition and a corresponding experimental research on an example of the MNIST data set. Some practical details for creating the Deep Neural Network and image recognition in the Caffe Framework are given as well.

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