Image Inpainting for Irregular Holes Using Extreme Learning Machine-Reference-Cited by-同舟云学术

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Image Inpainting for Irregular Holes Using Extreme Learning Machine

Published:2020-07-19 Issue: Volume: Page:69-81
ISSN:1860-949X
Container-title:Studies in Computational Intelligence
language:
Short-container-title:

Author:

Kanhar Debanand,Chandak Raunak

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-50641-4_5

Reference29 articles.

1. Zhang, A., Zhou, H., Li, X., & Zhu, W. (2019). Fast and robust learning in spiking feed-forward neural networks based on intrinsic plasticity mechanism. Neurocomputing, 365, 102–112.

2. Zhang, C., Zhang, X., & Zhang, Y. (2018). Dynamic properties of feed-forward neural networks and application in contrast enhancement for image. Chaos, Solitons & Fractals, 114, 281–290.

3. Shukla, S., & Raghuwanshi, B. S. (2019). Online sequential class-specific extreme learning machine for binary imbalanced learning. Neural Networks, 119, 235–248.

4. Chen, J., Zeng, Y., Li, Y., & Huang, G. B. (2019). Unsupervised feature selection based extreme learning machine for clustering. Neurocomputing., 386, 198–207.

5. Ashour, A. S., Samanta, S., Dey, N., Kausar, N., Abdessalemkaraa, W. B., & Hassanien, A. E. (2015). Computed tomography image enhancement using cuckoo search: A log transform based approach. Journal of Signal and Information Processing, 6(03), 244.

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1. An Image Inpainting Method Based on Whale-Integrated Monarch Butterfly Optimization-Based DCNN;International Journal of Swarm Intelligence Research;2022-07-13

2. Squiride Rank;International Journal of Web Portals;2022-05-13

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