Training Feed-Forward Neural Networks Employing Improved Bat Algorithm for Digital Image Compression-Reference-Cited by-同舟云学术

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Training Feed-Forward Neural Networks Employing Improved Bat Algorithm for Digital Image Compression

Published:2018 Issue: Volume: Page:315-323
ISSN:0302-9743
Container-title:Large-Scale Scientific Computing
language:
Short-container-title:

Author:

Alihodzic Adis

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-73441-5_33

Reference20 articles.

1. Bovik, A.: Handbook of Image and Video Processing, 2nd edn. Academic Press, University of Texas, Austin (2005)

2. Shukla, J., Alwani, M., Tiwari, A.K.: A survey on lossless image compression methods. In: Proceedings of 2nd International Conference on Computer Engineering and Technology (ICCET), vol. 6, pp. 136–141. IEEE, Chengdu (2010)

3. Miaou, S.-G., Lin, C.-L.: A quality-on-demand algorithm for wavelet-based compression of electrocardiogram signals. IEEE Trans. Biomed. Eng. 49(3), 233–239 (2002)

4. Yang, J., Zhu, G., Shi, Y.-Q.: Analyzing the effect of JPEG compression on local variance of image intensity. IEEE Trans. Image Process. 25(6), 2647–2656 (2006)

5. Tsolakis, D., Tsekouras, G.E., Niros, A.D., Rigos, A.: On the systematic development of fast fuzzy vector quantization for grayscale image compression. J. Neural Netw. 36, 83–96 (2012)

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