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» Learning with Few Examples by Transferring Feature Relevance
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PG
2002
IEEE
15 years 8 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
15 years 5 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
16 years 5 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
15 years 4 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
16 years 4 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