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» Actively Selecting Annotations Among Objects and Attributes
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PRIB
2010
Springer
242views Bioinformatics» more  PRIB 2010»
13 years 4 months ago
Consensus of Ambiguity: Theory and Application of Active Learning for Biomedical Image Analysis
Abstract. Supervised classifiers require manually labeled training samples to classify unlabeled objects. Active Learning (AL) can be used to selectively label only “ambiguous...
Scott Doyle, Anant Madabhushi
WWW
2007
ACM
14 years 6 months ago
Adding Value to Biodiversity Images Through Community Annotation
Morphbank, an on-line collection of museum-quality biological images, is an NSF funded project designed to facilitate the on-line collaboration of biologists from around the world...
Gregory A. Riccardi
ICPR
2010
IEEE
13 years 10 months ago
Active Boosting for Interactive Object Retrieval
This paper presents a new algorithm based on boosting for interactive object retrieval in images. Recent works propose ”online boosting” algorithms where weak classifier sets...
Alexis Lechervy, Philippe Henri Gosselin, Frederic...
CVPR
2011
IEEE
13 years 3 months ago
Dynamic Batch Mode Active Learning
Active learning techniques have gained popularity in reducing human effort to annotate data instances for inducing a classifier. When faced with large quantities of unlabeled dat...
Shayok Chakraborty, Vineeth Balasubramanian, Sethu...
CVPR
2012
IEEE
11 years 8 months ago
Discovering localized attributes for fine-grained recognition
Attributes are visual concepts that can be detected by machines, understood by humans, and shared across categories. They are particularly useful for fine-grained domains where c...
Kun Duan, Devi Parikh, David J. Crandall, Kristen ...