Self-stacking random weight neural network with multi-layer features fusion-Reference-Cited by-同舟云学术

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Self-stacking random weight neural network with multi-layer features fusion

Published:2022-03-11 Issue:7 Volume:13 Page:1945-1957
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Fu Aimin,Liu Jingna,Zhang Tian-Lun^ORCID

Funder

Innovative Research Group Project of the National Natural Science Foundation of China

National Natural Sci-ence Foundation of China

Guangdong Province Introduction of Innovative R&D Team

the project of State Key Lab- oratory of Mechanical Behavior and System Safety of Trac Engineering Structures, Shijiazhuang Tiedao Uni-versity

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

https://link.springer.com/content/pdf/10.1007/s13042-021-01498-z.pdf

Reference41 articles.

1. Zhang T, Yang X, Wang X, Wan R (2020) Deep joint neural model for single image haze removal and color correction. Inf Sci 541:16–35

2. Yu D, Hinton G, Morgan N, Chien J-T, Sagayama S (2012) Introduction to the special section on deep learning for speech and language processing. IEEE Trans Audio Speech Lang Process 20:4–6

3. Khobahi S, Soltanalian M (2020) Model-based deep learning for one-bit compressive sensing. IEEE Trans Signal Process 68:5292–5307

4. Fang F, Li J, Zeng T (2020) Soft-edge assisted network for single image super-resolution. IEEE Trans Image Process 29:4656–4668

5. LeCun Y, Bengio Y, Hinton G (2015) Deep learning. Nature 25:436

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