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» A testing scenario for probabilistic processes
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CVIU
2008
188views more  CVIU 2008»
13 years 8 months ago
Learning function-based object classification from 3D imagery
We propose a novel scheme for using supervised learning for function-based classification of objects in 3D images. During the learning process, a generic multi-level hierarchical ...
Michael Pechuk, Octavian Soldea, Ehud Rivlin
PAMI
2007
166views more  PAMI 2007»
13 years 8 months ago
A Bayesian, Exemplar-Based Approach to Hierarchical Shape Matching
—This paper presents a novel probabilistic approach to hierarchical, exemplar-based shape matching. No feature correspondence is needed among exemplars, just a suitable pairwise ...
Dariu Gavrila
ICSE
2004
IEEE-ACM
14 years 8 months ago
Skoll: Distributed Continuous Quality Assurance
Quality assurance (QA) tasks, such as testing, profiling, and performance evaluation, have historically been done in-house on developer-generated workloads and regression suites. ...
Atif M. Memon, Adam A. Porter, Cemal Yilmaz, Adith...
RSS
2007
152views Robotics» more  RSS 2007»
13 years 10 months ago
Dimensionality Reduction Using Automatic Supervision for Vision-Based Terrain Learning
Abstract— This paper considers the problem of learning to recognize different terrains from color imagery in a fully automatic fashion, using the robot’s mechanical sensors as ...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
ICASSP
2010
IEEE
13 years 8 months ago
Semi-Supervised Fisher Linear Discriminant (SFLD)
Supervised learning uses a training set of labeled examples to compute a classifier which is a mapping from feature vectors to class labels. The success of a learning algorithm i...
Seda Remus, Carlo Tomasi