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» Evaluating algorithms that learn from data streams
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AAAI
2012
13 years 10 months ago
Discovering Constraints for Inductive Process Modeling
Scientists use two forms of knowledge in the construction of explanatory models: generalized entities and processes that relate them; and constraints that specify acceptable combi...
Ljupco Todorovski, Will Bridewell, Pat Langley
TIP
2008
169views more  TIP 2008»
15 years 7 months ago
Weakly Supervised Learning of a Classifier for Unusual Event Detection
In this paper, we present an automatic classification framework combining appearance based features and Hidden Markov Models (HMM) to detect unusual events in image sequences. One...
Mark Jager, Christian Knoll, Fred A. Hamprecht
PAMI
2010
181views more  PAMI 2010»
15 years 6 months ago
Using Language to Learn Structured Appearance Models for Image Annotation
Abstract— Given an unstructured collection of captioned images of cluttered scenes featuring a variety of objects, our goal is to simultaneously learn the names and appearances o...
Michael Jamieson, Afsaneh Fazly, Suzanne Stevenson...
AMFG
2005
IEEE
203views Biometrics» more  AMFG 2005»
16 years 1 months ago
Learning to Fuse 3D+2D Based Face Recognition at Both Feature and Decision Levels
2D intensity images and 3D shape models are both useful for face recognition, but in different ways. While algorithms have long been developed using 2D or 3D data, recently has see...
Stan Z. Li, ChunShui Zhao, Meng Ao, Zhen Lei
198
Voted
UIST
2004
ACM
16 years 1 months ago
Hierarchical parsing and recognition of hand-sketched diagrams
A long standing challenge in pen-based computer interaction is the ability to make sense of informal sketches. A main difficulty lies in reliably extracting and recognizing the i...
Levent Burak Kara, Thomas F. Stahovich