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Transformation Across Deep Learning Frameworks

Transformation Across Deep Learning Frameworks
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Copyright: 2020
Pages: 48
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.ch003

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Abstract

Since the presented approach uses MatConvNet of Matlab as a preliminary training platform, the pre-trained CNN model of MatConvNet cannot be directly integrated into the Xcode platform currently. Therefore, developers need a third-party platform as a bridge, so that developers can transfer the model of Matlab to the Xcode environment and finally mount the model to an app for executing and testing on the iOS device. Apple provides developers with Core ML Tools to support the Caffe framework. Therefore, developers can convert the Caffe model into the ML model through Core ML Tools. Moreover, the Caffe provides MatCaffe for connecting Matlab and Caffe. It is apparent that developers can achieve the goal through these two bridges.

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