An end-to-end stereo matching algorithm based on improved convolutional neural network-Reference-Cited by-同舟云学术

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An end-to-end stereo matching algorithm based on improved convolutional neural network

Published:2020 Issue:6 Volume:17 Page:7787-7803
ISSN:1551-0018
Container-title:Mathematical Biosciences and Engineering
language:en
Short-container-title:

Author:

Liu Yan, ,Lv Bingxue,Wang Yuheng,Huang Wei

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modelling and Simulation,General Medicine

Link

http://www.aimspress.com/article/10.3934/mbe.2020396/pdf

Reference11 articles.

1. B. Sayed, I. Traoré, A. Abdelhalim,

2. S. O. Escolano, C. Rhemann, S. R. Fanello, W. Chang, A. Kowdle, Y. Degtyarev, et al.,

3. Z. Song, High-speed 3D shape measurement with structured light

4. A. L. Webber, J. M. Wood, B. Thompson, E. E Birch, From suppression to

5. C. Le, L. Xin,

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1. Optimization of greenhouse tomato localization in overlapping areas;Alexandria Engineering Journal;2023-03

2. Bi-window based stereo matching using combined Siamese convolutional neural network;Thirteenth International Conference on Digital Image Processing (ICDIP 2021);2021-06-30

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