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» Variational Relevance Vector Machines
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3DPVT
2006
IEEE
197views Visualization» more  3DPVT 2006»
13 years 11 months ago
Aerial LiDAR Data Classification Using Support Vector Machines (SVM)
We classify 3D aerial LiDAR scattered height data into buildings, trees, roads, and grass using the Support Vector Machine (SVM) algorithm. To do so we use five features: height, ...
Suresh K. Lodha, Edward J. Kreps, David P. Helmbol...
CVPR
2004
IEEE
14 years 9 months ago
3D Human Pose from Silhouettes by Relevance Vector Regression
We describe a learning based method for recovering 3D human body pose from single images and monocular image sequences. Our approach requires neither an explicit body model nor pr...
Ankur Agarwal, Bill Triggs
IJCNN
2006
IEEE
14 years 1 months ago
Non-Relevance Feedback Document Retrieval based on One Class SVM and SVDD
— This paper reports a new document retrieval method using non-relevant documents. Especially, this paper reports a comparison of retrieval efficiency between One Class Support ...
Takashi Onoda, Hiroshi Murata, Seiji Yamada
ICMCS
2005
IEEE
229views Multimedia» more  ICMCS 2005»
14 years 1 months ago
A methodology for improving recognition rate of linear discriminant analysis in video-based face recognition using support vecto
This paper proposes a two-step methodology for improving the discriminatory power of Linear Discriminant Analysis (LDA) for video-based human face recognition. Results indicate th...
Sreekar Krishna, Sethuraman Panchanathan
EPIA
2009
Springer
14 years 2 months ago
Classifying Documents According to Locational Relevance
This paper presents an approach for categorizing documents according to their implicit locational relevance. We report a thorough evaluation of several classifiers designed for th...
Ivo Anastácio, Bruno Martins, Pável ...