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检索条件"机构=a Geospatial Data Analytics Lab"
23 条 记 录,以下是21-30 订阅
排序:
A Review of Landcover Classification with Very-High Resolution Remotely Sensed Optical Images—Analysis Unit, Model Scalability and Transferability
arXiv
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arXiv 2022年
作者: Qin, Rongjun Liu, Tao Geospatial Data Analytics Lab The Ohio State University 218B Bolz Hall 2036 Neil Avenue ColumbusOH43210 United States Department of Civil Environmental and Geodetic Engineering The Ohio State University 2070 Neil Avenue ColumbusOH43210 United States Department of Electrical and Computer Engineering The Ohio State University 205 Dreese Labs 2015 Neil Avenue ColumbusOH43210 United States Translational Data Analytics Institute The Ohio State University Pomerene Hall 1760 Neil Ave ColumbusOH43210 United States College of Forest Resources and Environmental Science Michigan Technological University 1400 Townsend Drive HoughtonMI49931 United States Ecosystem Science Center Michigan Technological University 1400 Townsend Drive HoughtonMI49931 United States
As an important application in remote sensing, landcover classification remains one of the most challenging tasks in very-high-resolution (VHR) image analysis. As the rapidly increasing number of Deep Learning (DL) ba... 详细信息
来源: 评论
Trail configurational attributes and visitors’ spatial distribution in natural recreation area  12
Trail configurational attributes and visitors’ spatial dist...
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12th International Space Syntax Symposium, SSS 2019
作者: Zhai, Yujia Baran, Perver Korça College of Architecture and Urban Planning Big Data and Urban Spatial Analytics LAB Tongji University Shanghai China No.1239 Siping Road Yangpu District Shanghai200092 China Center for Geospatial Analytics College of Natural Resources College of Design North Carolina State University NC United States Box 7106 Jordan Hall RaleighNC27695-7106 United States
Visitors’ expectations for social interactions in natural recreation area is diverse;for instance, some seek solitude experience, while others may expect high level of social contacts. Better understanding of users’... 详细信息
来源: 评论
Towards a deep learning powered query engine for urban planning  21
Towards a deep learning powered query engine for urban plann...
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21st International Conference on Asian Language Processing, IALP 2017
作者: Shin, Teo Yon Zihong, Yuan Siong, Ng Wee Yangfan, Zhang Phangt, Valerie Data Analytics Department Institute for Infocomm Research ASTAR Singapore Singapore Information Systems and Geospatial Group Digital Planning Lab URA Singapore Singapore
Urban planning is crucial to sustainable growth. In order for the planners to make informed decisions, data from multiple sources have to be retrieved and cross-referenced efficiently. We discuss the implementation of... 详细信息
来源: 评论