HOW MANY MORE IMAGES DO WE NEED? PERFORMANCE PREDICTION OF BOOTSTRAPPING FOR IMAGE CLASSIFICATION

E Chatzilari; S Nikolopoulos; Y Kompatsiaris; J Kittler

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HOW MANY MORE IMAGES DO WE NEED? PERFORMANCE PREDICTION OF BOOTSTRAPPING FOR IMAGE CLASSIFICATION

E Chatzilari, S Nikolopoulos, Y Kompatsiaris and J Kittler

2014 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), pp.4256-4260

IEEE International Conference on Image Processing (ICIP) (Paris, FRANCE, 27/10/2014 - 30/10/2014)

01/01/2014

Abstract

Science & Technology

Technology

Computer Science

Theory & Methods

Engineering

Electrical & Electronic

Imaging Science & Photographic Technology

Computer Science

Engineering

scalable concept detection

image classification

performance prediction

bootstrapping

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Title: HOW MANY MORE IMAGES DO WE NEED? PERFORMANCE PREDICTION OF BOOTSTRAPPING FOR IMAGE CLASSIFICATION
Creators: E Chatzilari
S Nikolopoulos
Y Kompatsiaris
J Kittler
Contributors: IEEE (Publisher)
Publication Details: 2014 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), pp.4256-4260
Conference: IEEE International Conference on Image Processing (ICIP) (Paris, FRANCE, 27/10/2014 - 30/10/2014)
Date published: 01/01/2014
Date submitted: 17/05/2017
Identifiers: 99516124602346
Academic Unit: University of Surrey
Resource Type: Conference presentation

HOW MANY MORE IMAGES DO WE NEED? PERFORMANCE PREDICTION OF BOOTSTRAPPING FOR IMAGE CLASSIFICATION

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