Active learning with ensembles for image classification

Huan Liu; A. Mandvikar; P. Foschi; K. Torkkola

Active learning with ensembles for image classification

Huan Liu, A. Mandvikar, P. Foschi, K. Torkkola

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In many real-world tasks of image classification, limited amounts of labeled data are available to train automatic classifiers. Consequently, extensive human expert involvement is required for verification. A novel solution is presented that makes use of active learning combined with an ensemble of classifiers for each class. The result is a significant reduction in required expert involvement for uncertain image region classification.

Original language	English (US)
Title of host publication	IJCAI International Joint Conference on Artificial Intelligence
Pages	1435-1436
Number of pages	2
State	Published - 2003
Event	18th International Joint Conference on Artificial Intelligence, IJCAI 2003 - Acapulco, Mexico Duration: Aug 9 2003 → Aug 15 2003

Other

Other	18th International Joint Conference on Artificial Intelligence, IJCAI 2003
Country/Territory	Mexico
City	Acapulco
Period	8/9/03 → 8/15/03

ASJC Scopus subject areas

Artificial Intelligence

Cite this

@inproceedings{48d335a2f5714bbabea318bceb5673fc,

title = "Active learning with ensembles for image classification",

abstract = "In many real-world tasks of image classification, limited amounts of labeled data are available to train automatic classifiers. Consequently, extensive human expert involvement is required for verification. A novel solution is presented that makes use of active learning combined with an ensemble of classifiers for each class. The result is a significant reduction in required expert involvement for uncertain image region classification.",

author = "Huan Liu and A. Mandvikar and P. Foschi and K. Torkkola",

year = "2003",

language = "English (US)",

pages = "1435--1436",

booktitle = "IJCAI International Joint Conference on Artificial Intelligence",

note = "18th International Joint Conference on Artificial Intelligence, IJCAI 2003 ; Conference date: 09-08-2003 Through 15-08-2003",

}

TY - GEN

T1 - Active learning with ensembles for image classification

AU - Liu, Huan

AU - Mandvikar, A.

AU - Foschi, P.

AU - Torkkola, K.

PY - 2003

Y1 - 2003

N2 - In many real-world tasks of image classification, limited amounts of labeled data are available to train automatic classifiers. Consequently, extensive human expert involvement is required for verification. A novel solution is presented that makes use of active learning combined with an ensemble of classifiers for each class. The result is a significant reduction in required expert involvement for uncertain image region classification.

AB - In many real-world tasks of image classification, limited amounts of labeled data are available to train automatic classifiers. Consequently, extensive human expert involvement is required for verification. A novel solution is presented that makes use of active learning combined with an ensemble of classifiers for each class. The result is a significant reduction in required expert involvement for uncertain image region classification.

UR - http://www.scopus.com/inward/record.url?scp=47649103195&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=47649103195&partnerID=8YFLogxK

M3 - Conference contribution

SP - 1435

EP - 1436

BT - IJCAI International Joint Conference on Artificial Intelligence

T2 - 18th International Joint Conference on Artificial Intelligence, IJCAI 2003

Y2 - 9 August 2003 through 15 August 2003

ER -

Active learning with ensembles for image classification

Abstract

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ASJC Scopus subject areas

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