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» A testing scenario for probabilistic processes
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CVIU
2008
188views more  CVIU 2008»
15 years 1 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»
15 years 25 days 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
16 years 1 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»
15 years 2 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
15 years 1 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