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iOS App and Architecture of Convolutional Neural Networks

iOS App and Architecture of Convolutional Neural Networks
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Copyright: 2020
Pages: 22
Source title: MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition: Emerging Research and Opportunities
Source Author(s)/Editor(s): Jiann-Ming Wu (National Dong Hwa University, Taiwan) and Chao-Yuan Tien (National Dong Hwa University, Taiwan)
DOI: 10.4018/978-1-7998-1554-9.ch001

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Abstract

Deep convolutional neural networks (CNN) have attracted many attentions of researchers in the field of artificial intelligence. Based on several well-known architectures, more researchers and designers have joined the field of applying deep learning and devising a large number of CNNs for processing datasets of interesting. Equipped with modern audio, video, screen-touching components, and other sensors for online pattern recognition, the iOS mobile devices provide developers and users friendly testing and powerful computing environments. This chapter introduces the trend of developing pattern recognition CNN Apps on iOS devices and the neural organization of convolutional neural networks. Deep learning in Matlab and executing CNN models on iOS devices are introduced following the motivation of combining mathematical modelling and computation with neural architectures for developing pattern recognition iOS apps. This chapter also gives contexts of discussing typical hidden layers in the CNN architecture.

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