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Statistical classification / Geomorphology / Support vector machines / Regression analysis / Least squares support vector machine / LIDAR / Digital elevation model / Topography / Kernel principal component analysis / Statistics / Machine learning / Cartography


International Journal of Remote Sensing Vol. 30, No. 21, 10 November 2009, 5669–5683 Adaptive mapped least squares SVM-based smooth fitting method for DSM generation of LIDAR data
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Document Date: 2012-10-13 23:31:10

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Country

China / /

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Facility

College of Electrical Engineering / Institute of Intelligent Vision / China Three Gorges University / Huazhong University of Science / Hong Kong Polytechnic University / /

IndustryTerm

interpolation and smoothing solutions / triangular irregular networks / radial basis function network / proposed fitting algorithms / satellite image / potential solution / satellite orbit / scalar product / explicit solution / kernel-based algorithms / /

Organization

China Three Gorges University / WENZHONG SHI*† / SHENG ZHENG†‡§ and YAN TIAN†§ †Advanced Research Center for Spatial Information Technology / International Society for Photogrammetry and Remote Sensing / Huazhong University of Science and Technology / Wuhan / China §Electronic and Information Engineering Department / College of Electrical Engineering and Information Technology / Hong Kong Polytechnic University / Remote Sensing / Department of Land Surveying and Geo-Informatics / Institute of Intelligent Vision and Image Information / Hong Kong Polytechnic University / Hong Kong / /

Person

YAN TIAN / /

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Position

*Corresponding author / /

ProgrammingLanguage

C / /

Technology

kernel-based algorithms / laser / Remote Sensing / Information Technology / proposed fitting algorithms / LIDAR technology / /

URL

http /

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