Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Hwisong Kim"'
Publikováno v:
IEEE Access, Vol 12, Pp 163465-163480 (2024)
Bridge detection using Synthetic Aperture Radar (SAR) is important for infrastructure management, disaster prevention, and navigation automation. Although high-resolution SAR is becoming increasingly accessible, exploiting Sentinel-1 remains advantag
Externí odkaz:
https://doaj.org/article/918fb04ab814407f891e1a0ad535caa4
Publikováno v:
Remote Sensing, Vol 14, Iss 24, p 6373 (2022)
Satellite-based flood monitoring for providing visual information on the targeted areas is crucial in responding to and recovering from river floods. However, such monitoring for practical purposes has been constrained mainly by obtaining and analyzi
Externí odkaz:
https://doaj.org/article/b82bab0659b042d28f533289e12673a6
Autor:
Junwoo Kim, Hwisong Kim, Hyungyun Jeon, Seung-Hwan Jeong, Juyoung Song, Suresh Krishnan Palanisamy Vadivel, Duk-jin Kim
Publikováno v:
Remote Sensing, Vol 13, Iss 23, p 4759 (2021)
Deep learning is a promising method for image classification, including satellite images acquired by various sensors. However, the synergistic use of geospatial data for water body extraction from Sentinel-1 data using deep learning and the applicabi
Externí odkaz:
https://doaj.org/article/4ff38125ce4d40fa8a659c4c31146744
Publikováno v:
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::53fb0654a44fd2794e831713483ec7fc
https://doi.org/10.1109/igarss46834.2022.9883968
https://doi.org/10.1109/igarss46834.2022.9883968
Autor:
Seung-Hwan Jeong, Hwisong Kim, Junwoo Kim, Duk-jin Kim, Juyoung Song, Hyungyun Jeon, Suresh Krishnan Palanisamy Vadivel
Publikováno v:
Remote Sensing; Volume 13; Issue 23; Pages: 4759
Remote Sensing, Vol 13, Iss 4759, p 4759 (2021)
Remote Sensing, Vol 13, Iss 4759, p 4759 (2021)
Deep learning is a promising method for image classification, including satellite images acquired by various sensors. However, the synergistic use of geospatial data for water body extraction from Sentinel-1 data using deep learning and the applicabi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97bc2af68b3c5109fc35fc7580e6c2a8