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pro vyhledávání: '"Hyperspectral images (HSI)"'
Akademický článek
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Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 921-934 (2025)
In hyperspectral images, the high dimensionality of spectral data often leads to redundant spectral information, making it difficult to extract features. Two-dimensional CNNs fail to effec-tively extract spatial and spectral information, and deployin
Externí odkaz:
https://doaj.org/article/e3d278e8a8854c84bb51dc554d046655
Autor:
Chuanliang Sun, Weixin Zhang, Genping Zhao, Qian Wu, Wanjie Liang, Ni Ren, Hongxin Cao, Lidong Zou
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
Aboveground biomass (AGB) is a key indicator of crop nutrition and growth status. Accurately and timely obtaining biomass information is essential for crop yield prediction in precision management systems. Remote sensing methods play a key role in mo
Externí odkaz:
https://doaj.org/article/c36598d7069b4a759b18d76df7e24085
Publikováno v:
AIMS Mathematics, Vol 8, Iss 11, Pp 27989-28009 (2023)
Synthesizing hyperspectral images (HSI) from an ordinary camera has been accomplished recently. However, such computation models require detailed properties of the target camera, which can only be measured in a professional lab. This prerequisite pre
Externí odkaz:
https://doaj.org/article/9c36bd0947394cbdafc292f74cd90334
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 1523-1534 (2024)
Hyperspectral change detection (CD) aims to obtain the change information of objects in the multitemporal hyperspectral images (HSIs). Recently, with the advantages in fully extracting the image features of irregular areas, the graph convolutional ne
Externí odkaz:
https://doaj.org/article/d87083d30df349abb14ef5d126014b4f
Autor:
Jain, Pallavi
Publikováno v:
Dissertations
Cancer detection has been a great topic of research for a long time, as early detection of cancer can help in increasing the survival rate of patients by providing on time better treatment. A robust system is required in order to detect early-stage c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::81ca651c7c2f09fe43d8878531fa8dd1
Publikováno v:
IEEE Access, Vol 10, Pp 39533-39544 (2022)
This paper introduces a novel and efficient Graph Convolutional Network (GCN) and Spatial Supporting Modification (SSM) method for classifying Hyperspectral Images (HSI), called Spatial First (SPA-F). The proposed method can utilize spatial informati
Externí odkaz:
https://doaj.org/article/f1add7386f3a424eb08f82ec174351b7
Autor:
Phaneendra Kumar, B. L. N.1 (AUTHOR) blnphaneendra@kluniversity.in, Vaddi, Radhesyam2 (AUTHOR) syam.radhe@vrsiddhartha.ac.in, Manoharan, Prabukumar3 (AUTHOR) mprabukumar@vit.ac.in, Agilandeeswari, L.3 (AUTHOR) agila.l@vit.ac.in, Sangeetha, V.3 (AUTHOR) sangeetha.v2022@vitstudent.ac.in
Publikováno v:
Scientific Reports. 12/30/2024, Vol. 14 Issue 1, p1-21. 21p.
Autor:
Zhao, Ziqi1 (AUTHOR) zhaozq22@mails.jlu.edu.cn, Yang, Changbao1 (AUTHOR) yangcb@jlu.edu.cn, Qiu, Zhongjun2 (AUTHOR) qiuzhongjun@jlssy.com, Wu, Qiong1 (AUTHOR) wuqiong@jlu.edu.cn
Publikováno v:
Remote Sensing. Nov2024, Vol. 16 Issue 22, p4270. 23p.
Autor:
Zhang, Yong1 (AUTHOR), Peng, Yishu1 (AUTHOR) lovepys@hnist.edu.cn, Zhang, Guoyun1 (AUTHOR), Li, Wujin1 (AUTHOR)
Publikováno v:
International Journal of Remote Sensing. Sep2024, Vol. 45 Issue 18, p6759-6786. 28p.