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Название: Guide to Convolutional Neural Networks
Год: 2017
Издатель: Springer International Publishing
Язык: english
Кол-во страниц: 273
Формат: PDF
Описание:
This must-read text/reference introduces the fundamental concepts of convolutional neural networks (ConvNets), offering practical guidance on using libraries to implement ConvNets in applications of traffic sign detection and classification. The work presents techniques for optimizing the computational efficiency of ConvNets, as well as visualization techniques to better understand the underlying processes. The proposed models are also thoroughly evaluated from different perspectives, using exploratory and quantitative analysis.
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Название: Guide to Convolutional Neural Networks
Год: 2017
Издатель: Springer International Publishing
Язык: english
Кол-во страниц: 273
Формат: PDF
Описание:
This must-read text/reference introduces the fundamental concepts of convolutional neural networks (ConvNets), offering practical guidance on using libraries to implement ConvNets in applications of traffic sign detection and classification. The work presents techniques for optimizing the computational efficiency of ConvNets, as well as visualization techniques to better understand the underlying processes. The proposed models are also thoroughly evaluated from different perspectives, using exploratory and quantitative analysis.
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