Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Shuaidong Jia"'
Publikováno v:
Journal of Marine Science and Engineering, Vol 12, Iss 6, p 980 (2024)
Addressing the shortcomings of existing ship trajectory compression methods that rely on the empirical setting of a fixed threshold and face challenges in controlling the spatial similarity before and after compression, this paper proposes a self-ada
Externí odkaz:
https://doaj.org/article/8713b49504834be2b93159ac5e82ffe5
Publikováno v:
Journal of Geodesy and Geoinformation Science, Vol 3, Iss 2, Pp 93-104 (2020)
For the current automatic coastline generalization method, only one-line element is considered separately, but the relationship between the nearby elements is not effectively considered. A synergistic simplification method for multiple coastlines bas
Externí odkaz:
https://doaj.org/article/11874e9770ec4da396373ed2f9ab9ec9
Publikováno v:
Journal of Geodesy and Geoinformation Science, Vol 2, Iss 4, Pp 10-20 (2019)
The current underwater terrain surface matching algorithm, which uses Hu moment as the similarity index, cannot gain accurate location due to the algorithm's disadvantage in detecting slight differences. To solve this problem, a line-surface integrat
Externí odkaz:
https://doaj.org/article/108481eeda004e068082f45852c775b9
Publikováno v:
International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a664913bbff32ce06834ef2b0eebce7d
https://doi.org/10.1117/12.2667680
https://doi.org/10.1117/12.2667680
Publikováno v:
2022 3rd International Conference on Geology, Mapping and Remote Sensing (ICGMRS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::24d8b09153615ac5852963843daefa4a
https://doi.org/10.1109/icgmrs55602.2022.9849245
https://doi.org/10.1109/icgmrs55602.2022.9849245
Publikováno v:
International Conference on Computer Vision and Pattern Analysis (ICCPA 2021).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::251f8a3b24b205743b3d798313a6b3cd
https://doi.org/10.1117/12.2627440
https://doi.org/10.1117/12.2627440
Publikováno v:
Marine Geodesy. 43:189-212
Existing methods for automatically selecting islands for nautical charts utilize the Voronoi diagram. However, we will show that the Voronoi diagrams cannot accurately represent the density and distribution of islands in cartographic generalization,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9e3bcc0f35d40b67170acd5d9233ca7
https://doi.org/10.1080/01490419.2019.1707335
https://doi.org/10.1080/01490419.2019.1707335
Publikováno v:
IABSE Congress Reports.
Computer vision has become an effective way to collect the information of traffic load, which is crucial for bridge statistical analysis, safety evaluation, and maintenance strategies. To obtain the information of vehicles such as position and wheelb
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e918e4a47b2248d08e1deedc1e1ec2d9
https://doi.org/10.2749/ghent.2021.0459
https://doi.org/10.2749/ghent.2021.0459
Publikováno v:
Journal of Navigation. 72:430-446
Due to the limitations of the existing methods (for example, the route binary tree method) that can only automatically generate routes based on a single chart, a method for automatically generating the shortest distance route based on an obstacle spa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6e282bd998627f6cad9dbf3be7f8e370
https://doi.org/10.1017/s0373463318000814
https://doi.org/10.1017/s0373463318000814
Publikováno v:
Marine Geodesy. 39:256-270
To address the limitations of manually selecting aids to navigation (AtNs) on charts, a method for automatically selecting AtNs based on their spatial influence domains (SIDs) is proposed. First, the associations between the spatial attributes of an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::658e8f3a81e885445f8f7ac77e687ce8
https://doi.org/10.1080/01490419.2016.1173144
https://doi.org/10.1080/01490419.2016.1173144