Zobrazeno 1 - 10
of 120
pro vyhledávání: '"Yao-Yi Chiang"'
Autor:
Lourdes Johanna Avelar Portillo, Georgia L. Kayser, Charlene Ko, Angelica Vasquez, Jimena Gonzalez, Diego Jose Avelar, Nayib Alvarenga, Meredith Franklin, Yao-Yi Chiang
Publikováno v:
International Journal for Equity in Health, Vol 22, Iss 1, Pp 1-19 (2023)
Abstract Background Access to water and sanitation is a basic human right; however, in many parts of the world, communities experience water, sanitation, and hygiene (WaSH) insecurity. While WaSH insecurity is prevalent in many low and middle-income
Externí odkaz:
https://doaj.org/article/e7f7a5d526c14c22951b96a5bab5f8a5
Autor:
Kenan Li, Katherine Sward, Huiyu Deng, John Morrison, Rima Habre, Meredith Franklin, Yao-Yi Chiang, Jose Luis Ambite, John P. Wilson, Sandrah P. Eckel
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Abstract Advances in measurement technology are producing increasingly time-resolved environmental exposure data. We aim to gain new insights into exposures and their potential health impacts by moving beyond simple summary statistics (e.g., means, m
Externí odkaz:
https://doaj.org/article/384a2716062c4903b9f6a54dd833d875
Publikováno v:
IEEE Access, Vol 8, Pp 6978-6996 (2020)
Information extraction from historical maps represents a persistent challenge due to inferior graphical quality and the large data volume of digital map archives, which can hold thousands of digitized map sheets. Traditional map processing techniques
Externí odkaz:
https://doaj.org/article/8fb6daa8dd2d44d5bbf6fab661df7a8b
Publikováno v:
IEEE Access, Vol 7, Pp 40649-40662 (2019)
Extracting residential areas from historical raster topographic maps benefits to analyze land type change. The existing algorithms have the shortcomings including easily misidentifying objects and low positional accuracy of the identified boundary, s
Externí odkaz:
https://doaj.org/article/d195a545ad8a4350b830015ba327af26
Publikováno v:
Environmental Health, Vol 17, Iss 1, Pp 1-6 (2018)
Abstract Geospatial artificial intelligence (geoAI) is an emerging scientific discipline that combines innovations in spatial science, artificial intelligence methods in machine learning (e.g., deep learning), data mining, and high-performance comput
Externí odkaz:
https://doaj.org/article/c8ed3d41e1a64cf3b7707ae84ef09430
Publikováno v:
IEEE Access, Vol 6, Pp 4904-4915 (2018)
Matching spatial entities (e.g., polygonal residential areas) from sources of significantly different map scales is challenging. The reason is that the same entities in two map scales have significant variations in their positions, structure shapes a
Externí odkaz:
https://doaj.org/article/f9f0c57f1cec44399487cc6cb80f6947
Autor:
Johannes H. Uhl, Stefan Leyk, Zekun Li, Weiwei Duan, Basel Shbita, Yao-Yi Chiang, Craig A. Knoblock
Publikováno v:
Remote Sensing, Vol 13, Iss 18, p 3672 (2021)
Spatially explicit, fine-grained datasets describing historical urban extents are rarely available prior to the era of operational remote sensing. However, such data are necessary to better understand long-term urbanization and land development proce
Externí odkaz:
https://doaj.org/article/4a4516931e8546aa963a9afdf2b2ccd1
Autor:
Kenan Li, Huiyu Deng, John Morrison, Rima Habre, Meredith Franklin, Yao-Yi Chiang, Katherine Sward, Frank D. Gilliland, José Luis Ambite, Sandrah P. Eckel
Publikováno v:
Sensors, Vol 21, Iss 17, p 5801 (2021)
Many approaches to time series classification rely on machine learning methods. However, there is growing interest in going beyond black box prediction models to understand discriminatory features of the time series and their associations with outcom
Externí odkaz:
https://doaj.org/article/88d185a851354246a0357154dd6264f8
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 7, Iss 4, p 148 (2018)
Historical maps are unique sources of retrospective geographical information. Recently, several map archives containing map series covering large spatial and temporal extents have been systematically scanned and made available to the public. The geog
Externí odkaz:
https://doaj.org/article/e53c1685e8a4419e885dab2d4fbdb5e0
Publikováno v:
IEEE Transactions on Smart Grid. 14:2446-2459