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ECCV
2008
Springer
16 years 1 months ago
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...
ICMLA
2009
14 years 9 months ago
Learning Probabilistic Structure Graphs for Classification and Detection of Object Structures
Abstract--This paper presents a novel and domainindependent approach for graph-based structure learning. The approach is based on solving the Maximum Common SubgraphIsomorphism pro...
Johannes Hartz
IPMI
2007
Springer
16 years 21 days ago
Robust Parametric Modeling Approach Based on Domain Knowledge for Computer Aided Detection of Vertebrae Column Metastases in MRI
This study evaluates a robust parametric modeling approach for computer-aided detection (CAD) of vertebrae column metastases in whole-body MRI. Our method involves constructing a m...
Anna K. Jerebko, G. P. Schmidt, Xiang Sean Zhou, J...
COLT
1992
Springer
15 years 4 months ago
Language Learning from Stochastic Input
Language learning from positive data in the Gold model of inductive inference is investigated in a setting where the data can be modeled as a stochastic process. Specifically, the...
Shyam Kapur, Gianfranco Bilardi
ICIP
2004
IEEE
16 years 1 months ago
A probabilistic framework for object recognition in video
We propose a solution to the problem of object recognition given a continuous video sequence containing multiple views of an object. Initially, object models are acquired from ima...
Omar Javed, Mubarak Shah, Dorin Comaniciu