Zobrazeno 1 - 10
of 30 276
pro vyhledávání: '"Endmember"'
Autor:
Wang, Li1 (AUTHOR) lily@xaau.edu.cn, Bi, Yang1 (AUTHOR), Wang, Wei1 (AUTHOR), Li, Junfang1 (AUTHOR)
Publikováno v:
Scientific Reports. 8/2/2024, Vol. 14 Issue 1, p1-42. 42p.
Autor:
Yang, Lifeng1 (AUTHOR) lifengyang@mail.sitp.ac.cn, Song, Xiaorui1 (AUTHOR), Bai, Bin1 (AUTHOR), Chen, Zhuo1 (AUTHOR)
Publikováno v:
Remote Sensing. Jun2024, Vol. 16 Issue 12, p2245. 26p.
Autor:
He, Jingping1 (AUTHOR) deanriley1@arizona.edu, Riley, Dean N.1 (AUTHOR), Barton, Isabel1 (AUTHOR)
Publikováno v:
Remote Sensing. Jun2024, Vol. 16 Issue 12, p2137. 28p.
This work proposes a variational inference (VI) framework for hyperspectral unmixing in the presence of endmember variability (HU-EV). An EV-accounted noisy linear mixture model (LMM) is considered, and the presence of outliers is also incorporated i
Externí odkaz:
http://arxiv.org/abs/2407.14899
The rheological behaviour of olivine deforming by dislocation creep controls geodynamic processes that involve steady-state flow or transient viscosity evolution. Longstanding rheological models applied to both contexts assume that dislocation creep
Externí odkaz:
http://arxiv.org/abs/2406.10076
Publikováno v:
MNRAS 513, 363-373 (2022)
The diverse isotopic anomalies of meteorites demonstrate that the protoplanetary disk was composed of components from different stellar sources, which mixed in the disk and formed the planetary bodies. However, the origin of the accretion materials o
Externí odkaz:
http://arxiv.org/abs/2407.14817
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-42 (2024)
Abstract Based on double-compressed sampling, a hyperspectral spectral unmixing algorithm (SU_DCS) is proposed, which could directly complete the endmember extraction and abundance estimation. On the basis of the linear mixed model (LMM), we designed
Externí odkaz:
https://doaj.org/article/cd9f68fea0994785a5e54725d0bd7f51
Autor:
Mizutani, Tomohiko
Hyperspectral imaging technology has a wide range of applications, including forest management, mineral resource exploration, and Earth surface monitoring. Endmember extraction of hyperspectral images is a key step in leveraging this technology for a
Externí odkaz:
http://arxiv.org/abs/2404.13098
Autor:
Ratnayake, R. M. K. L., Sumanasekara, D. M. U. P., Wickramathilaka, H. M. K. D., Godaliyadda, G. M. R. I., Ekanayake, M. P. B., Herath, H. M. V. R.
In recent years, transformer-based deep learning networks have gained popularity in Hyperspectral (HS) unmixing applications due to their superior performance. The attention mechanism within transformers facilitates input-dependent weighting and enha
Externí odkaz:
http://arxiv.org/abs/2402.03835
Given a hyperspectral image, the problem of hyperspectral unmixing (HU) is to identify the endmembers (or materials) and the abundance (or endmembers' contributions on pixels) that underlie the image. HU can be seen as a matrix factorization problem
Externí odkaz:
http://arxiv.org/abs/2401.14592