AlgaeNet: A Deep-Learning Framework to Detect Floating Green Algae From Optical and SAR Imagery-Reference-Cited by-同舟云学术

AlgaeNet: A Deep-Learning Framework to Detect Floating Green Algae From Optical and SAR Imagery

Published:2022 Issue: Volume:15 Page:2782-2796
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Gao Le¹^ORCID,Li Xiaofeng¹^ORCID,Kong Fanzhou²,Yu Rencheng²,Guo Yuan¹,Ren Yibin¹^ORCID

Affiliation:

1. Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, CAS and Center for Ocean Mega-Science, CAS, Qingdao, China

2. Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, CAS and Center for Ocean Mega-Science, CAS, Qingdao, China

Funder

National Natural Science Foundation of China

Major Scientific and Technological Innovation Projects in Shandong Province

Strategic Priority Research Program of the Chinese Academy of Sciences

Center for Ocean Mega-Science

CAS Program

Zhejiang Provincial Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

Reference44 articles.

5. Branching phenotype and plasticity in floating ecotype of Ulva prolifera (Ulvophyceae, Chlorophyta);ma;Mar Sci,2020

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