Unsupervised convolutional neural networks for large-scale image clustering

Chih Chung Hsu, Chia Wen Lin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

The paper proposes an unsupervised convolutional neural network (UCNN) to solve clustering and representation learning jointly in an iterative manner. The key idea behind the proposed method is that learning better feature representations of images leads to more accurate image clustering results, whereas better image clustering can benefit the feature learning with the proposed UCNN. In the proposed method, given an input image set, we first randomly pick k samples and extract their features as the initial centroids of image clusters using the proposed UCNN with an initial representation model pre-trained from the ImageNet dataset. Mini-batch k-means is then performed to assign cluster labels to individual input samples for a mini-batch of images randomly sampled from the input image set until all images are processed. Subsequently, UCNN simultaneously updates the parameters of UCNN and the centroids of image clusters iteratively based on stochastic gradient descent. Experimental results demonstrate the proposed method outperforms start-of-the-art clustering schemes in terms of accuracy and memory complexity on large-scale image sets containing millions of images.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings
PublisherIEEE Computer Society
Pages390-394
Number of pages5
ISBN (Electronic)9781509021758
DOIs
Publication statusPublished - 2018 Feb 20
Event24th IEEE International Conference on Image Processing, ICIP 2017 - Beijing, China
Duration: 2017 Sep 172017 Sep 20

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2017-September
ISSN (Print)1522-4880

Conference

Conference24th IEEE International Conference on Image Processing, ICIP 2017
Country/TerritoryChina
CityBeijing
Period17-09-1717-09-20

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Fingerprint

Dive into the research topics of 'Unsupervised convolutional neural networks for large-scale image clustering'. Together they form a unique fingerprint.

Cite this