Chlorophyll-a Retrieval From Sentinel-2 Images Using Convolutional Neural Network Regression-Reference-Cited by-同舟云学术

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Chlorophyll-a Retrieval From Sentinel-2 Images Using Convolutional Neural Network Regression

Published:2022 Issue: Volume:19 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Aptoula Erchan^ORCID,Ariman Sema^ORCID

Funder

Tubitak Grant

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/9651998/09404297.pdf?arnumber=9404297

Cited by 27 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. Smartphone as an alternative to measure chlorophyll-a concentration in small waterbodies;Journal of Environmental Management;2024-09

2. Global deep learning model for delineation of optically shallow and optically deep water in Sentinel-2 imagery;Remote Sensing of Environment;2024-09

3. Research on the Inversion of Chlorophyll-a Concentration in the Hong Kong Coastal Area Based on Convolutional Neural Networks;Journal of Marine Science and Engineering;2024-07-03

4. Lake total suspended matter retrieval by wind speed: A machine learning model trained by time-series satellite imagery;Ecological Informatics;2024-07

5. Chlorophyll-a Estimation in 149 Tropical Semi-Arid Reservoirs Using Remote Sensing Data and Six Machine Learning Methods;Remote Sensing;2024-05-24

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