Zobrazeno 1 - 5
of 5
pro vyhledávání: '"C. J. Della Porta"'
Autor:
C. J. Della Porta, Chein-I Chang
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 11775-11788 (2021)
Compressive sensing (CS) has received considerable interest in hyperspectral sensing. Recent articles have also exploited the benefits of CS in hyperspectral image classification (HSIC) in the compressively sensed band domain (CSBD). However, on many
Externí odkaz:
https://doaj.org/article/0300165fe8e54dc8aea522834b537f60
Autor:
Chein-I Chang, C. J. Della Porta
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 59:2378-2390
Compressive sensing (CS) has recently been demonstrated as an enabling technology for hyperspectral sensing on remote and autonomous platforms. The power, on-board storage, and computation requirements associated with the high dimensionality of hyper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::28c6f7b6b3a4c2ac70f0e11fc8673e15
https://doi.org/10.1109/tgrs.2020.3000873
https://doi.org/10.1109/tgrs.2020.3000873
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 58:1087-1101
N-finder algorithm (N-FINDR) has been widely used for finding endmembers in hyperspectral imagery. Since N-FINDR must find all endmembers simultaneously, it requires exhausting all possible $p$ -endmember combinations among the entire data samples wi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3fdb08f3d0c67bea9bc85b5ecba00360
https://doi.org/10.1109/tgrs.2019.2943448
https://doi.org/10.1109/tgrs.2019.2943448
Publikováno v:
Big Data: Learning, Analytics, and Applications.
Although hyperspectral technology has continued to improve over the years, its use is often still limited due to size, weight and power (SWaP) constraints. One of the more taxing requirements, is the need to sample a large number of very fine spectra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eeabe83a2b8699ee545293af10c03ef0
https://doi.org/10.1117/12.2518382
https://doi.org/10.1117/12.2518382
Publikováno v:
The Journal of the Acoustical Society of America. 144:1684-1684
Uncertainty in a sound speed profile can lead to uncertainty in the associated prediction of transmission loss (TL). In order to better quantify the effect of imperfect knowledge of the sound speed profile on the acoustic propagation, a study was don
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e01d9493e8fabeeeb39ad537c8526e35
https://doi.org/10.1121/1.5067489
https://doi.org/10.1121/1.5067489