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» Group-based learning: a boosting approach
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TMI
2010
172views more  TMI 2010»
14 years 8 months ago
Comparison of AdaBoost and Support Vector Machines for Detecting Alzheimer's Disease Through Automated Hippocampal Segmentation
Abstract— We compared four automated methods for hippocampal segmentation using different machine learning algorithms (1) hierarchical AdaBoost, (2) Support Vector Machines (SVM)...
Jonathan H. Morra, Zhuowen Tu, Liana G. Apostolova...
90
Voted
ICIP
2010
IEEE
14 years 7 months ago
A supervised micro-calcification detection approach in digitised mammograms
We present in this paper a supervised approach for automatic detection of micro-calcifications. The system is based on learning the different morphology of the micro-calcification...
Albert Torrent, Arnau Oliver, Xavier Lladó,...
ICML
2007
IEEE
15 years 10 months ago
Learning for efficient retrieval of structured data with noisy queries
Increasingly large collections of structured data necessitate the development of efficient, noise-tolerant retrieval tools. In this work, we consider this issue and describe an ap...
Charles Parker, Alan Fern, Prasad Tadepalli
MIR
2004
ACM
236views Multimedia» more  MIR 2004»
15 years 3 months ago
Boosting contextual information in content-based image retrieval
We present a new framework for characterizing and retrieving objects in cluttered scenes. This CBIR system is based on a new representation describing every object taking into acc...
Jaume Amores, Nicu Sebe, Petia Radeva, Theo Gevers...
114
Voted
CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
14 years 11 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang