Deep-sea Nodule Mineral Image Segmentation Algorithm Based on Pix2PixHD-Reference-Cited by-同舟云学术

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Deep-sea Nodule Mineral Image Segmentation Algorithm Based on Pix2PixHD

Published:2022 Issue:1 Volume:73 Page:1449-1462
ISSN:1546-2226
Container-title:Computers, Materials & Continua
language:en
Short-container-title:

Author:

Song Wei,Wang Haolin,Zhang Xinping,Xia Jianxin,Liu Tongmu,Shi Yuxi

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Mechanics of Materials,Modeling and Simulation,Biomaterials

Link

https://www.techscience.com/cmc/v73n1/47807/pdf

Reference28 articles.

1. Manganese nodules in Chile, an alternative for the production of Co and Mn in the future—A review;Toro;Minerals,2020

2. Tighten regulations on deep-sea mning;Van Dover;Nature,2011

3. The progress in the investigation and study of global deep-sea polymetallic nodules;Yu;Geology in China,2018

4. Generative adversarial nets;Goodfellow,2014

5. Fine-scale microbial communities associated with manganese nodules in deep-sea sediment of the korea deep ocean study area in the northeast equatorial pacific;Cho;Ocean Science Journal,2018

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Prediction of the Pore-Pressure Built-Up and Temperature of Fire-Loaded Concrete with Pix2Pix;Computers, Materials & Continua;2024

2. Deep learning in image segmentation for mineral production: A review;Computers & Geosciences;2023-11

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