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» Neural networks for HREM image analysis
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NIPS
1998
13 years 8 months ago
Learning to Estimate Scenes from Images
We seek the scene interpretation that best explains image data. For example, we may want to infer the projected velocities (scene) which best explain two consecutive image frames ...
William T. Freeman, Egon C. Pasztor
JMLR
2008
188views more  JMLR 2008»
13 years 7 months ago
Maximal Causes for Non-linear Component Extraction
We study a generative model in which hidden causes combine competitively to produce observations. Multiple active causes combine to determine the value of an observed variable thr...
Jörg Lücke, Maneesh Sahani
ICDAR
1999
IEEE
13 years 11 months ago
Multifont Classification using Typographical Attributes
This paper introduces a multifont classification scheme to help recognition of multifont and multisize characters. It uses typographical attributes such as ascenders, descenders a...
Min-Chul Jung, Yong-Chul Shin, Sargur N. Srihari
CAIP
2009
Springer
114views Image Analysis» more  CAIP 2009»
13 years 10 months ago
Decision Trees Using the Minimum Entropy-of-Error Principle
Binary decision trees based on univariate splits have traditionally employed so-called impurity functions as a means of searching for the best node splits. Such functions use estim...
Joaquim Marques de Sá, João Gama, Ra...
CIVR
2008
Springer
182views Image Analysis» more  CIVR 2008»
13 years 9 months ago
Fusion of audio and visual cues for laughter detection
Past research on automatic laughter detection has focused mainly on audio-based detection. Here we present an audiovisual approach to distinguishing laughter from speech and we sh...
Stavros Petridis, Maja Pantic