Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Arpan Man Sainju"'
Publikováno v:
Frontiers in Big Data, Vol 4 (2021)
Spatial classification with limited observations is important in geographical applications where only a subset of sensors are deployed at certain spots or partial responses are collected in field surveys. For example, in observation-based flood inund
Externí odkaz:
https://doaj.org/article/54c6a6f88c4347c6933929d0ab1e6d09
Publikováno v:
ACM Transactions on Intelligent Systems and Technology. 13:1-22
Given earth imagery with spectral features on a terrain surface, this paper studies surface segmentation based on both explanatory features and surface topology. The problem is important in many spatial and spatiotemporal applications such as flood e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e5375ddd3ef53a1c792db28bc721d1db
https://doi.org/10.1145/3481043
https://doi.org/10.1145/3481043
Publikováno v:
Proceedings of the 2023 SIAM International Conference on Data Mining (SDM) ISBN: 9781611977653
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::194f6c972e5c8e84e32bed30d25250f9
https://doi.org/10.1137/1.9781611977653.ch36
https://doi.org/10.1137/1.9781611977653.ch36
Autor:
Saugat Adhikari, Da Yan, Mirza Tanzim Sami, Jalal Khalil, Lyuheng Yuan, Bhadhan Roy Joy, Zhe Jiang, Arpan Man Sainju
Publikováno v:
Proceedings of the 30th International Conference on Advances in Geographic Information Systems.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8b4c631d1b37a0821cf253f884ce0811
https://doi.org/10.1145/3557915.3560962
https://doi.org/10.1145/3557915.3560962
Autor:
Zhe Jiang, Arpan Man Sainju
Publikováno v:
International Journal of Remote Sensing. 42:1160-1179
Flood extent mapping plays a crucial role in disaster management and national water forecasting. In recent years, high-resolution optical imagery becomes increasingly available with the deployment of numerous small satellites and drones. However, ana
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6bf7b71ec61486f08762eb7634859106
https://doi.org/10.1080/01431161.2020.1823514
https://doi.org/10.1080/01431161.2020.1823514
Autor:
Arpan Man Sainju, Zhe Jiang
Publikováno v:
ACM/IMS Transactions on Data Science. 1:1-20
Each year, around 6 million car accidents occur in the U.S. on average. Road safety features (e.g., concrete barriers, metal crash barriers, rumble strips) play an important role in preventing or mitigating vehicle crashes. Accurate maps of road safe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::195630dc3b729f1a2644e6409cd32ece
https://doi.org/10.1145/3362069
https://doi.org/10.1145/3362069
Publikováno v:
IEEE Transactions on Big Data. 6:107-118
Colocation patterns refer to subsets of spatial features whose instances are frequently located together. Mining colocation patterns is important in many applications such as identifying relationships between diseases and environmental factors, but i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::345567e4249605cd3111a9009cc0a98f
https://doi.org/10.1109/tbdata.2018.2871062
https://doi.org/10.1109/tbdata.2018.2871062
Publikováno v:
Frontiers in Big Data, Vol 4 (2021)
Frontiers in Big Data
Frontiers in Big Data
Spatial classification with limited observations is important in geographical applications where only a subset of sensors are deployed at certain spots or partial responses are collected in field surveys. For example, in observation-based flood inund
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b95e13892f1132093a65007bcf007d47
https://www.frontiersin.org/articles/10.3389/fdata.2021.707951/full
https://www.frontiersin.org/articles/10.3389/fdata.2021.707951/full
Publikováno v:
ACM Transactions on Intelligent Systems and Technology. 10:1-25
Class ambiguity refers to the phenomenon whereby similar features correspond to different classes at different locations. Given heterogeneous geographic data with class ambiguity, the spatial ensemble learning (SEL) problem aims to find a decompositi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::21bf7d04fe44b2d0981cdd0d463167a4
https://doi.org/10.1145/3337798
https://doi.org/10.1145/3337798
Publikováno v:
Proceedings of the 2021 SIAM International Conference on Data Mining (SDM) ISBN: 9781611976700
SDM
SDM
Given a 3D surface defined by an elevation function on a 2D grid as well as non-spatial features observed at each pixel, the problem of surface segmentation aims to classify pixels into contiguous classes based on both non-spatial features and surfac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f3c9575747e0e4a43763cb5e93e9935f
https://doi.org/10.1137/1.9781611976700.29
https://doi.org/10.1137/1.9781611976700.29