CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 深度强化学习
Image Clustering based on Deep Sparse Representations
Lv Le1; Zhao Dongbin1; Deng QingQiong2
2017-02
Conference NameThe 2016 IEEE Symposium Series on Computational Intelligence
Conference Date6-9 Dec. 2016
Conference PlaceAthens, Greece
AbstractCurrently, the supervised trained deep neural networks (DNNs) have been successfully applied in several image classification tasks. However, how to extract powerful data representations and discover semantic concepts from unlabeled data is a more practical issue. Unsupervised feature learning methods aim at extracting abstract representations from unlabeled data. Large amount of research works illustrate that these representations can be directly used in the supervised tasks. However, due to the high dimensionality of these representations, it is difficult to discover the categorical concepts among them in an unsupervised way. In this paper, we propose combining the winner-take-all autoencoder with the bipartite graph partitioning algorithm to cluster unlabeled image data. The winner-take-all autoencoder can learn the additive sparse representations. By the experiments, we present the properties of the sparse representations. The bipartite graph partitioning can take full advantage of them and generate semantic clusters. We discover that the confident instances in each cluster are well discriminated. Based on the initial clustering result, we further train a support vector machine (SVM) to refine the clusters. Our method can discover the categorical concepts rapidly and the experiment shows that the clustering performance of our method is good.
DOI10.1109/SSCI.2016.7850110
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Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14471
Collection复杂系统管理与控制国家重点实验室_深度强化学习
Affiliation1.The State Key Laboratory of Management and Control for Complex Systems Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
2.College of Information Science and Technology, Beijing Normal University, Beijing, 100875, China
Recommended Citation
GB/T 7714
Lv Le,Zhao Dongbin,Deng QingQiong. Image Clustering based on Deep Sparse Representations[C],2017.
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