Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Yesid Fonseca"'
Publikováno v:
Journal of Agriculture and Food Research, Vol 14, Iss , Pp 100793- (2023)
Cultivation of the Horvin plum is one of the main economic activities in the region of Márquez, in the department of Boyacá, in Colombia. However, its selection process, which needs to be optimized and improved, is still done manually and leads to
Externí odkaz:
https://doaj.org/article/5957dd50cd2e4ce9b29720ef4129e284
Autor:
Oscar Yesid Fonseca-Roa
Publikováno v:
Urbano, Vol 25, Iss 46 (2022)
El patrimonio urbano es una categoría del patrimonio cultural. Los centros históricos están protegidos por un marco jurídico que salvaguarda los valores que son objeto de la declaratoria correspondiente. El estudio de la política de protección
Externí odkaz:
https://doaj.org/article/a2a10a9412744aee840948c421d558b0
Supplementary Material
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1bde83d13e939a50df9c1e39fb6691a5
Publikováno v:
2020 IEEE Colombian Conference on Applications of Computational Intelligence (IEEE ColCACI 2020).
The tensor completion problem solves the recovery of corrupted data in a multidimensional array named as a tensor. The traditional approaches in tensor completion are based on the transform tensor singular value decomposition(tt-SVD). These approache
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8ea1bf529829cff92eece899793fc188
https://doi.org/10.1109/colcaci50549.2020.9247929
https://doi.org/10.1109/colcaci50549.2020.9247929
Publikováno v:
Imaging and Applied Optics Congress.
A state-of-the-art deep learning framework, HyperReconNet, recover an spectral image from its compressed measurements. However, HyperReconNet does not take the sensing matrix into a account on the training. We propose a residual modbased convolutiona
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::150831c9e10a80397b442ad4288c94d3
https://doi.org/10.1364/3d.2020.jth2a.35
https://doi.org/10.1364/3d.2020.jth2a.35
Publikováno v:
EUSIPCO
This paper proposes a low-rank tensor minimization algorithm to recover a spectral image (SI) from a set of compressed observations. The proposal takes advantage of the transform tensor singular value decomposition (tt-SVD) to promote a low-rank stru
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa3bd96eec7f94c865c98d8863eca75e
https://doi.org/10.23919/eusipco.2019.8902654
https://doi.org/10.23919/eusipco.2019.8902654
Publikováno v:
Applied Optics. 60:4197
Compressive spectral imaging (CSI) has emerged as an alternative spectral image acquisition technology, which reduces the number of measurements at the cost of requiring a recovery process. In general, the reconstruction methods are based on handcraf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b214e3df289fbcdbc134d8a1ce65286b
https://doi.org/10.1364/ao.420305
https://doi.org/10.1364/ao.420305
Publikováno v:
EUSIPCO
Compressive cameras acquire measurements of a scene using random projections instead of sampling at Nyquist rate. Several reconstruction algorithms have been proposed, taking advantage of previous knowledge about the scene. However, some inference ta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3008a683ebc72bf46ce754d0bf9f8658
https://doi.org/10.23919/eusipco.2018.8553312
https://doi.org/10.23919/eusipco.2018.8553312