Advancing Airborne Hyperspectral Data Processing and Applications for Sustainable Agriculture Using RTM-Based Machine Learning

Qu Zhou, Sheng Wang, Kaiyu Guan

Research output: Contribution to book/anthology/report/proceeding › Article in proceedings › Research › peer-review

Original language	Undefined/Unknown
Title of host publication	IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
Number of pages	4
Publisher	IEEE
Publication date	2023
Pages	1269-1272
ISBN (Print)	979-8-3503-3174-5
ISBN (Electronic)	979-8-3503-2010-7, 979-8-3503-2009-1
DOIs	https://doi.org/10.1109/IGARSS52108.2023.10283455
Publication status	Published - 2023

Series	IEEE International Geoscience and Remote Sensing Symposium proceedings
ISSN	2153-6996

Access to Document

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title = "Advancing Airborne Hyperspectral Data Processing and Applications for Sustainable Agriculture Using RTM-Based Machine Learning",

author = "Qu Zhou and Sheng Wang and Kaiyu Guan",

year = "2023",

doi = "10.1109/IGARSS52108.2023.10283455",

language = "Udefineret/Ukendt",

isbn = "979-8-3503-3174-5",

series = "IEEE International Geoscience and Remote Sensing Symposium proceedings",

publisher = "IEEE",

pages = "1269--1272",

booktitle = "IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium",

}

Zhou, Q, Wang, S & Guan, K 2023, Advancing Airborne Hyperspectral Data Processing and Applications for Sustainable Agriculture Using RTM-Based Machine Learning. in IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium. IEEE, IEEE International Geoscience and Remote Sensing Symposium proceedings, pp. 1269-1272. https://doi.org/10.1109/IGARSS52108.2023.10283455

Advancing Airborne Hyperspectral Data Processing and Applications for Sustainable Agriculture Using RTM-Based Machine Learning. / Zhou, Qu; Wang, Sheng; Guan, Kaiyu.
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2023. p. 1269-1272 (IEEE International Geoscience and Remote Sensing Symposium proceedings).

Research output: Contribution to book/anthology/report/proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Advancing Airborne Hyperspectral Data Processing and Applications for Sustainable Agriculture Using RTM-Based Machine Learning

AU - Zhou, Qu

AU - Wang, Sheng

AU - Guan, Kaiyu

PY - 2023

Y1 - 2023

U2 - 10.1109/IGARSS52108.2023.10283455

DO - 10.1109/IGARSS52108.2023.10283455

M3 - Konferencebidrag i proceedings

SN - 979-8-3503-3174-5

T3 - IEEE International Geoscience and Remote Sensing Symposium proceedings

SP - 1269

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BT - IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium

PB - IEEE

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Zhou Q, Wang S, Guan K. Advancing Airborne Hyperspectral Data Processing and Applications for Sustainable Agriculture Using RTM-Based Machine Learning. In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium. IEEE. 2023. p. 1269-1272. (IEEE International Geoscience and Remote Sensing Symposium proceedings). doi: 10.1109/IGARSS52108.2023.10283455