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Model selection / Statistical classification / Geostatistics / Segmentation / Support vector machine / Spectral clustering / Cluster analysis / Region growing / Feature selection / Statistics / Image processing / Machine learning


Tree Detection in Urban Regions Using Aerial LiDAR and Image Data John Secord and Avideh Zakhor EECS Department, U.C. Berkeley {secord,avz}@eecs.berkeley.edu Abstract
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Document Date: 2006-12-16 19:39:58


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Seattle / Stuttgart / RANSAC / Landscape Assessment Freiburg / /

Company

Neural Information Processing Systems / Nikon / Airborne 1 Incorporated / Google / /

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Germany / Jordan / /

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M&A / /

Facility

U.C. Berkeley campus / Building Detection / Berkeley campus / University of California / University of California at Berkeley / /

IndustryTerm

segmentation algorithms / grid search / spectral clustering algorithm / region growing algorithm / learning spectral clustering algorithm / stereo imaging methods / processor server / segmentation algorithm / classification algorithms / parallel processing / region growing segmentation algorithm / above algorithm / polygonization algorithm / region-growing algorithm / learning algorithm / /

Organization

Video and Image Processing Lab / University of California / Avideh Zakhor EECS Department / University of California / Berkeley / Pattern Analysis and Machine Intelligence / /

Person

John Secord / /

ProgrammingLanguage

C / /

ProvinceOrState

California / Washington / /

PublishedMedium

IEEE Transactions on Pattern Analysis and Machine Intelligence / /

Technology

specific spectral clustering algorithm / learning algorithm / laser / above algorithm / Remote Sensing / weighted SVM algorithm / 3-D / segmentation algorithms / proposed algorithm / specific SVM algorithm / SVM algorithm / segmentation algorithm / fuzzy logic / training algorithm / classification algorithms / Image Processing / RANSAC-based polygonization algorithm / digital camera / polygonization algorithm / parallel processing / learning spectral clustering algorithm / /

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