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» Explanation-Based Learning for Image Understanding
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IDA
2008
Springer
13 years 7 months ago
Symbolic methodology for numeric data mining
Currently statistical and artificial neural network methods dominate in data mining applications. Alternative relational (symbolic) data mining methods have shown their effectivene...
Boris Kovalerchuk, Evgenii Vityaev
CVPR
2011
IEEE
13 years 3 months ago
A Segmentation-aware Object Detection Model with Occlusion Handling
The bounding box representation employed by many popular object detection models [3, 6] implicitly assumes all pixels inside the box belong to the object. This assumption makes th...
Tianshi Gao, Benjamin Packer, Daphne Koller
MICCAI
2010
Springer
13 years 5 months ago
Multi-Class Sparse Bayesian Regression for Neuroimaging Data Analysis
The use of machine learning tools is gaining popularity in neuroimaging, as it provides a sensitive assessment of the information conveyed by brain images. In particular, finding ...
Vincent Michel, Evelyn Eger, Christine Keribin, Be...
ICCV
2009
IEEE
15 years 13 days ago
Label Set Perturbation for MRF based Neuroimaging Segmentation
Graph-cuts based algorithms are effective for a variety of segmentation tasks in computer vision. Ongoing research is focused toward making the algorithms even more general, as ...
Dylan Hower, Vikas Singh, Sterling C. Johnson
IPMI
2003
Springer
14 years 8 months ago
Feature Selection for Shape-Based Classification of Biological Objects
Abstract. In this paper, feature selection methodology from the machine learning literature is applied to the problem of shape-based classification. This methodology discards stati...
Paul A. Yushkevich, Sarang C. Joshi, Stephen M. Pi...