Zobrazeno 1 - 5
of 5
pro vyhledávání: '"J. E. Cubillas"'
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-5-2024, Pp 33-39 (2024)
Land cover classification is critical in various fields, including environmental monitoring, urban planning, and ecological assessment, facilitating informed decision-making processes. Traditional land cover classification methods often involve labor
Externí odkaz:
https://doaj.org/article/95667691a7f6416b8292b7dbda89a71e
Autor:
J. E. Cubillas, R. Daguil
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-5-2024, Pp 25-31 (2024)
The digitization of maps poses a significant challenge for GIS operators and engineers, particularly in encoding bearings and distances into GIS software. This study, titled “Circinus: An AI-Based Technical Description Plotting,” represents a sub
Externí odkaz:
https://doaj.org/article/975ec3bb5a5e4140ad86e3563a46c552
Publikováno v:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol III-7, Pp 165-172 (2016)
This research describes the methods involved in the mapping of different high value crops in Agusan del Norte Philippines using LiDAR. This project is part of the Phil-LiDAR 2 Program which aims to conduct a nationwide resource assessment using LiDAR
Externí odkaz:
https://doaj.org/article/7d1661d4c8a845ff8a4b25db51c90f73
Autor:
J. E. Cubillas, M. Japitana
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLI-B7, Pp 189-194 (2016)
This study demonstrates the application of CIELAB, Color intensity, and One Dimensional Scalar Constancy as features for image recognition and classifying benthic habitats in an image with the coastal areas of Hinatuan, Surigao Del Sur, Philippines a
Externí odkaz:
https://doaj.org/article/1116aa19e6b54bbd81461747c3f8e232
Autor:
M. Japitana, J. E. Cubillas
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLI-B7, Pp 189-194 (2016)
This study demonstrates the application of CIELAB, Color intensity, and One Dimensional Scalar Constancy as features for image recognition and classifying benthic habitats in an image with the coastal areas of Hinatuan, Surigao Del Sur, Philippines a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62dd3737c7e52578f2ab796f7e3547bc
https://doi.org/10.5194/isprs-archives-xli-b7-189-2016
https://doi.org/10.5194/isprs-archives-xli-b7-189-2016