Deep Learning-Based Multiscale Pyramid Sieve and Analysis Module in Image Segmentation-Reference-Cited by-同舟云学术

Deep Learning-Based Multiscale Pyramid Sieve and Analysis Module in Image Segmentation

Author:

Cao Di¹^ORCID,Cao Jian-Nong²,Zhu Qian³,Lou Li-Jiao⁴,Xiao Nian-Zhong⁵

Affiliation:

1. School of Earth Science and Resources, Chang’an University, Xi’an, China

2. Key Laboratory of Degraded and Unused Land Consolidation Engineering, Ministry of Land and Resources, Xi’an, China

3. School of Geology Engineering and Geomatics, Chang’an University, Xi’an, China

4. Yellow River Hydrological Survey and Mapping Bureau, Zhengzhou, China

5. Fourth Geological Exploration Institute of Henan Geology and Mineral Bureau, Zhengzhou, China

Funder

National Natural Science Foundation of China

Key Laboratory of Degraded and Unused Land Consolidation Engineering of the Ministry of Land and Resources

Natural Science Basic Research Plan in Shaanxi Province of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference49 articles.

4. Bayesian SegNet: Model uncertainty in deep convolutional encoder–decoder architectures for scene understanding;kendall;Comput Sci,2015

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