Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Doudou Zeng"'
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 112, Iss , Pp 102968- (2022)
To meet the requirement of high-resolution and high-efficiency unmanned aerial vehicle (UAV)-borne multispectral remote sensing, using the miniaturized large-array commodity complementary metal-oxide semiconductor (CMOS) camera is an effective soluti
Externí odkaz:
https://doaj.org/article/cc89fbd777a34809bba25eac5202b20d
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 103, Iss , Pp 102504- (2021)
Surface reconstruction from a 3D point cloud is a long-standing problem in the field of computer graphics and vision, especially for point clouds that are sparse and noisy. To solve this problem, a novel method, termed LV-GCNN, that combines lossless
Externí odkaz:
https://doaj.org/article/811f4ec867284afa8181e134c1066f72
Publikováno v:
Sensors, Vol 20, Iss 22, p 6489 (2020)
Image matching forms an essential means of data association for computer vision, photogrammetry and remote sensing. The quality of image matching is heavily dependent on image details and naturalness. However, complex illuminations, denoting extreme
Externí odkaz:
https://doaj.org/article/0b9789c7574c449d86d625da3fd55d3f
Publikováno v:
Remote Sensing, Vol 12, Iss 14, p 2181 (2020)
The existing deep learning methods for point cloud classification are trained using abundant labeled samples and used to test only a few samples. However, classification tasks are diverse, and not all tasks have enough labeled samples for training. I
Externí odkaz:
https://doaj.org/article/b7c20da07d0644faadd30712bba036f4
Publikováno v:
Remote Sensing, Vol 12, Iss 2, p 311 (2020)
Urban land cover classification for high-resolution images is a fundamental yet challenging task in remote sensing image analysis. Recently, deep learning techniques have achieved outstanding performance in high-resolution image classification, espec
Externí odkaz:
https://doaj.org/article/0a4a7c777f3641e99216327371e1a726
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-15
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b870fdb8e22dac1a421a6432d94c4a3
https://doi.org/10.1109/tgrs.2022.3182776
https://doi.org/10.1109/tgrs.2022.3182776
Publikováno v:
ISPRS Journal of Photogrammetry and Remote Sensing. 171:367-384
Highly accurate 2D maps can supply basic geospatial information for efficient and accurate indoor building modeling. However, problematic scenarios, which are characterized by few features, similar components and large scales, seriously influence dat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4da5bfd1bf91f766d2e2d1d8e4fb1e96
https://doi.org/10.1016/j.isprsjprs.2020.11.004
https://doi.org/10.1016/j.isprsjprs.2020.11.004
Publikováno v:
Sensors, Vol 20, Iss 6489, p 6489 (2020)
Sensors (Basel, Switzerland)
Sensors
Volume 20
Issue 22
Sensors (Basel, Switzerland)
Sensors
Volume 20
Issue 22
Image matching forms an essential means of data association for computer vision, photogrammetry and remote sensing. The quality of image matching is heavily dependent on image details and naturalness. However, complex illuminations, denoting extreme
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f17c7c6bd4eec65cb7c91242244862a2
https://www.mdpi.com/1424-8220/20/22/6489
https://www.mdpi.com/1424-8220/20/22/6489
Publikováno v:
Remote Sensing, 12 (14)
Remote Sensing; Volume 12; Issue 14; Pages: 2181
Remote Sensing, Vol 12, Iss 2181, p 2181 (2020)
Remote Sensing; Volume 12; Issue 14; Pages: 2181
Remote Sensing, Vol 12, Iss 2181, p 2181 (2020)
The existing deep learning methods for point cloud classification are trained using abundant labeled samples and used to test only a few samples. However, classification tasks are diverse, and not all tasks have enough labeled samples for training. I
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::44da091384e753f36afd26a352eebbbd
https://hdl.handle.net/20.500.11850/429610
https://hdl.handle.net/20.500.11850/429610
Publikováno v:
Remote Sensing; Volume 12; Issue 2; Pages: 311
Remote Sensing, Vol 12, Iss 2, p 311 (2020)
Remote Sensing, Vol 12, Iss 2, p 311 (2020)
Urban land cover classification for high-resolution images is a fundamental yet challenging task in remote sensing image analysis. Recently, deep learning techniques have achieved outstanding performance in high-resolution image classification, espec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26a5dcfb4a6da679dc5d35fa60319798