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» Learning with Few Examples by Transferring Feature Relevance
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PG
2002
IEEE
15 years 2 months ago
Example-Based Caricature Generation with Exaggeration
In this paper, we present a system that automatically generates caricatures from input face images. From example caricatures drawn by an artist, our caricature system learns how a...
Lin Liang, Hong Chen, Ying-Qing Xu, Heung-Yeung Sh...
FLAIRS
2010
14 years 12 months ago
CsMTL MLP For WEKA: Neural Network Learning with Inductive Transfer
We present context-sensitive Multiple Task Learning, or csMTL as a method of inductive transfer. It uses additional contextual inputs along with other input features when learning ...
Liangliang Tu, Benjamin Fowler, Daniel L. Silver
ECCV
2008
Springer
15 years 11 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
2003
14 years 11 months ago
The Consolidation of Neural Network Task Knowledge
— Fundamental to the problem of lifelong machine learning is how to consolidate the knowledge of a learned task within a long-term memory structure (domain knowledge) without the...
Daniel L. Silver, Peter McCracken
ICIP
2003
IEEE
15 years 11 months ago
Kernel indexing for relevance feedback image retrieval
Relevance feedback is an attractive approach to developing flexible metrics for content-based retrieval in image and video databases. Large image databases require an index struct...
Jing Peng, Douglas R. Heisterkamp