Lightweight Convolutional Neural Network Architecture for Mobile Platforms

HU Ting,ZHU Yongxin,TIAN Li,FENG Songlin,WANG Hui

2019DOAJ (DOAJ: Directory of Open Access Journals)Computer Science被引 1

摘要

For the problem that the deep neural network has low accuracy and over-fitting on the mobile platforms,a lightweight Convolutional Neural Network(CNN) architecture is proposed.The 3×3 depthwise separable convolution replaces the standard 3×3 convolution kernel in the SqueezeNet network model basic module Fire,constructs the SparkNet network structure,and replaces the model convolution to obtain the network deformation structure.Experimental results show that compared with the SqueezeNet network structure,the architecture can improve the calculation speed of the network model,effectively reduce the network model size and reduce the number of parameters.

引用本文（GB/T 7714）

HU Ting,ZHU Yongxin,TIAN Li,FENG Songlin,WANG Hui. Lightweight Convolutional Neural Network Architecture for Mobile Platforms[J]. DOAJ (DOAJ: Directory of Open Access Journals), 2019.

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DOI：https://doi.org/10.19678/j.issn.1000-3428.0049905

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