A New Image Classification Approach via Improved MobileNet Models with Local Receptive Field Expansion in Shallow Layers
Joint Authors
Wang, Wei
Hu, Yiyang
Zou, Ting
Liu, Hongmei
Wang, Jin
Wang, Xin
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-01
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Because deep neural networks (DNNs) are both memory-intensive and computation-intensive, they are difficult to apply to embedded systems with limited hardware resources.
Therefore, DNN models need to be compressed and accelerated.
By applying depthwise separable convolutions, MobileNet can decrease the number of parameters and computational complexity with less loss of classification precision.
Based on MobileNet, 3 improved MobileNet models with local receptive field expansion in shallow layers, also called Dilated-MobileNet (Dilated Convolution MobileNet) models, are proposed, in which dilated convolutions are introduced into a specific convolutional layer of the MobileNet model.
Without increasing the number of parameters, dilated convolutions are used to increase the receptive field of the convolution filters to obtain better classification accuracy.
The experiments were performed on the Caltech-101, Caltech-256, and Tubingen animals with attribute datasets, respectively.
The results show that Dilated-MobileNets can obtain up to 2% higher classification accuracy than MobileNet.
American Psychological Association (APA)
Wang, Wei& Hu, Yiyang& Zou, Ting& Liu, Hongmei& Wang, Jin& Wang, Xin. 2020. A New Image Classification Approach via Improved MobileNet Models with Local Receptive Field Expansion in Shallow Layers. Computational Intelligence and Neuroscience،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1138852
Modern Language Association (MLA)
Wang, Wei…[et al.]. A New Image Classification Approach via Improved MobileNet Models with Local Receptive Field Expansion in Shallow Layers. Computational Intelligence and Neuroscience No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1138852
American Medical Association (AMA)
Wang, Wei& Hu, Yiyang& Zou, Ting& Liu, Hongmei& Wang, Jin& Wang, Xin. A New Image Classification Approach via Improved MobileNet Models with Local Receptive Field Expansion in Shallow Layers. Computational Intelligence and Neuroscience. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1138852
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1138852