Artificial Intelligence

   

How Deep Is Deep Enough? HDDE9-2S A CNN Network With 12 Layers Reached Higher Accuracy In Image Classification

Authors: Guangqun Chen

In this paper I studied SfNet further. I reduced layers of SfNet, created a group of networks: HDDE6 series and HDDE9 series. HDDE6-3 and HDDE6-2S have 9 layers, HDDE9-2 has 11 layers, HDDE9-2S and HDDE9-3 have 12 layers. In my experiments on dataset CALTECH-256, compared to SFNet, the classification accuracy of HDDE9-3 increases about 4.35%, the classification accuracy of HDDE9-2 increases about 3.07%, the classification accuracy of HDDE9-2S increases about 5.55%. Compared to VGG-16, the classification accuracy of HDDE9-3 increases from 83.63% to 90.73%, the classification accuracy of HDDE9-2 increases to 89.81%, the classification accuracy of HDDE9-2S increases to 92.28%. For HDDE6 series, features extraction part uses only 1 convolution layer and 5 MixedSCLayers, has much less parameters, running speed is much faster, the accuracy of HDDE6-3 is the same as HDDE9-3's on CALTECH-256. All the improvements are due to the use of Structure Composing Layers.

Comments: 10 Pages.

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Submission history

[v1] 2019-03-04 02:28:34
[v2] 2019-03-07 14:48:19
[v3] 2019-03-12 11:49:59
[v4] 2019-03-17 15:32:33

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