Author image not provided
 Mo Shan

Add personal information
  Affiliation history
Bibliometrics: publication history
Average citations per article1.33
Citation Count4
Publication count3
Publication years2012-2016
Available for download1
Average downloads per article209.00
Downloads (cumulative)209
Downloads (12 Months)37
Downloads (6 Weeks)4
Arrow RightAuthor only

See all colleagues of this author

See all subject areas


3 results found Export Results: bibtexendnoteacmrefcsv

Result 1 – 3 of 3
Sort by:

December 2016 IEEE Transactions on Circuits and Systems for Video Technology: Volume 26 Issue 12, December 2016
Publisher: IEEE Press
Citation Count: 0

Sparse coding (SC) is making a significant impact in computer vision and signal processing communities, which achieves the state-of-the-art performance in a variety of applications for images, e.g., denoising, restoration, and synthesis. We propose an adaptive and robust SC algorithm exploiting the characteristics of typical laser range data and the ...

2 published by ACM
August 2015 Journal on Computing and Cultural Heritage (JOCCH): Volume 8 Issue 4, August 2015
Publisher: ACM
Citation Count: 1
Downloads (6 Weeks): 4,   Downloads (12 Months): 37,   Downloads (Overall): 209

Full text available: PDFPDF
Inspired by the outstanding performance of sparse representation (SR) in a variety of image/video relevant classification and identification tasks, we propose an adaptive SR method for painting style analysis. Significantly improved over previous SR-based methods, which heavily rely on the comparison of query paintings, our method is able to authenticate ...
Keywords: discriminative patches, DCT baseline, Sparse representation, dictionary learning

October 2012 ECCV'12: Proceedings of the 12th European conference on Computer Vision - Volume Part V
Publisher: Springer-Verlag
Citation Count: 2

Recent evaluation of representative background subtraction techniques demonstrated the drawbacks of these methods, with hardly any approach being able to reach more than 50% precision at recall level higher than 90%. Challenges in realistic environment include illumination change causing complex intensity variation, background motions (trees, waves, etc.) whose magnitude can ...

The ACM Digital Library is published by the Association for Computing Machinery. Copyright © 2018 ACM, Inc.
Terms of Usage   Privacy Policy   Code of Ethics   Contact Us