Abstract
This paper presents briefly an incremental learning method based on SVM for online sketchy shape recognition. It can collect all classified results corrected by user and select some important samples as the retraining data according to their distance to the hyper-plane of the SVM-classifier. The classifier can then do incremental learning quickly on the newly added samples, and the retrained classifier can be adaptive to the user’s drawing styles. Experiment shows the effectiveness of the proposed method.
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References
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© 2005 Springer-Verlag Berlin Heidelberg
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Sun, Z., Zhang, L., Tang, E. (2005). An Incremental Learning Method Based on SVM for Online Sketchy Shape Recognition. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539087_82
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DOI: https://doi.org/10.1007/11539087_82
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28323-2
Online ISBN: 978-3-540-31853-8
eBook Packages: Computer ScienceComputer Science (R0)