Laser & Optoelectronics Progress, Volume. 58, Issue 6, 610016(2021)
Structured Deep Discriminant Embedded Coding Network for Image Clustering
Figures & Tables(11)
Fig. 5. Some samples in MNIST and Fashion-MNIST datasets. (a) MNIST dataset; (b) Fashion-MNIST dataset
Fig. 6. Distribution visualization of embedded subspaces of different strategies on the MNIST dataset. (a) ConvAE; (b) ConvAE+MI; (c) ConvAE+GCN; (d) ConvAE+MI+GCN
Fig. 7. Effect of different combinations of parameter λ1 and λ2 on the ACC and NMI on the Fashion-MNIST dataset. (a) Effect on ACC; (b) effect on NMI
Table 1. Dataset introduction
View tableTable 1. Dataset introduction
Dataset Number of samples Number of classes Dimension USPS 9298 10 1×16×16 MNIST 70000 10 1×28×28 Fashion-MNIST 70000 10 1×28×28
Table 2. Number of channels and core size of autoencoder network
View tableTable 2. Number of channels and core size of autoencoder network
Dataset Encoder-1/ Decoder-4 Encoder-2/ Decoder-3 Encoder-3/ Decoder-2 Encoder-4/ Decoder-1 USPS 3×3×16 3×3×32 MNIST 3×3×16 3×3×16 3×3×32 3×3×32 Fashion- MNIST 3×3×16 3×3×16 3×3×32 3×3×32
Table 3. Clustering results of different clustering algorithms on three datasets
View tableTable 3. Clustering results of different clustering algorithms on three datasets
Algorithm USPS MNIST Fashion-MNIST ACC NMI ACC NMI ACC NMI K-means 0.6682 0.6270 0.5322 0.5004 0.4742 0.5120 AE+K-means 0.6931 0.6620 0.8076 0.7303 0.5853 0.6142 DEC 0.7408 0.7529 0.8655 0.8372 0.5180 0.5462 IDEC 0.7605 0.7846 0.8806 0.8672 0.5291 0.5570 Deepcluster 0.5623 0.5403 0.7971 0.6615 0.5422 0.5100 SDCN 0.7789 0.7926 0.8530 0.8427 0.5780 0.6047 SDDECC 0.7986 0.8142 0.9022 0.8958 0.6171 0.6306
Table 4. Impact of different strategies on clustering performance
View tableTable 4. Impact of different strategies on clustering performance
Method USPS MNIST Fashion-MNIST ACC NMI ACC NMI ACC NMI ConvAE 0.6981 0.6519 0.7762 0.7450 0.5462 0.5563 ConvAE+MI 0.7853 0.7442 0.8350 0.8023 0.5922 0.6091 ConvAE+GCN 0.7822 0.7875 0.8574 0.8449 0.5843 0.6167 ConvAE+MI+GCN 0.7986 0.8142 0.9022 0.8958 0.6171 0.6306
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Fu Xingwu, Lü Mingming, Liu Wanjun, Wei Xian. Structured Deep Discriminant Embedded Coding Network for Image Clustering[J]. Laser & Optoelectronics Progress, 2021, 58(6): 610016
Paper Information
Category: Image Processing
Received: Aug. 11, 2020
Accepted: --
Published Online: Mar. 11, 2021
The Author Email: Lü Mingming (329010672@qq.com)
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