Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Aito Fujita"'
Autor:
Charlotte Bay Hasager, James Imber, Jana Fischereit, Aito Fujita, Krystallia Dimitriadou, Merete Badger
Publikováno v:
Wind Energy, Vol 27, Iss 11, Pp 1369-1387 (2024)
ABSTRACT Satellite synthetic aperture radar (SAR) provides ocean surface wind fields at 10 m above sea level. The objective is to investigate the capability of SAR satellite StriX observations for mapping offshore wind farm wakes. The focus is on the
Externí odkaz:
https://doaj.org/article/e010a813e07240f7893f45bd79cc8050
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 19016-19034 (2024)
This article presents a novel convolutional neural network (CNN) architecture for segmenting significantly small and crowded objects in remote sensing imagery. Although such small objects are characteristic in the remote sensing domain, the previous
Externí odkaz:
https://doaj.org/article/392afba74bf04e749727d35438465c30
Publikováno v:
Energies, Vol 16, Iss 9, p 3819 (2023)
The planning of offshore wind energy projects requires wind observations over long periods for the establishment of wind speed distributions. In the marine environment, high-quality in situ observations are sparse and restricted to point locations. N
Externí odkaz:
https://doaj.org/article/0f59387f40944764a33de74fe9eb5ae7
Autor:
Ryuhei Hamaguchi, Keisuke Nemoto, Masakazu Sato, Aito Fujita, Tomoyuki Imaizumi, Shuhei Hikosaka
Publikováno v:
Remote Sensing Technologies and Applications in Urban Environments II.
Building change information extracted from remote sensing imageries is important for various applications such as urban management and marketing planning. The goal of this work is to develop a methodology for automatically capturing building changes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3b44004acdd45abb675363be88582f1f
https://doi.org/10.1117/12.2277912
https://doi.org/10.1117/12.2277912
Publikováno v:
MVA
This paper explores the effective use of Convolutional Neural Networks (CNNs) in the context of washed-away building detection from pre- and post-tsunami aerial images. To this end, we compile a dedicated, labeled aerial image dataset to construct mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8fa5ff3f0a6348df1e96fb82426c551b
https://doi.org/10.23919/mva.2017.7986759
https://doi.org/10.23919/mva.2017.7986759
Publikováno v:
BMVC
Most of the traditional convolutional neural networks (CNNs) implements bottom-up approach (feed-forward) for image classifications. However, many scientific studies demonstrate that visual perception in primates rely on both bottom-up and top-down c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2583b8650d834f8a5957d402d0530e0
https://doi.org/10.5244/c.31.183
https://doi.org/10.5244/c.31.183
Publikováno v:
WACV
Thanks to recent advances in CNNs, solid improvements have been made in semantic segmentation of high resolution remote sensing imagery. However, most of the previous works have not fully taken into account the specific difficulties that exist in rem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4176fbb27c02c614b4d5cef26d201f49
Autor:
Keisuke Nemoto, Ryuhei Hamaguchi, Masakazu Sato, Aito Fujita, Tomoyuki Imaizumi, Shuhei Hikosaka
Publikováno v:
Proceedings of SPIE; 7/26/2017, Vol. 10431, p1-12, 12p