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Boosting multiple experts by joint optimisation of decision thresholds

Kittler, J, Yusoff, Y, Christmas, W, Windeatt, T and Windridge, D (2001) Boosting multiple experts by joint optimisation of decision thresholds Pattern Recognition and Image Analysis, 11, 3. pp. 529-541.

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We consider a multiple classifier system which combines the hard decisions of experts by voting. We argue that the individual experts should not set their own decision thresholds. The respective thresholds should be selected jointly as this will allow compensation of the weaknesses of some experts by the relative strengths of the others. We perform the joint optimization of decision thresholds for a multiple expert system by a systematic sampling of the multidimensional decision threshold space. We show the effectiveness of this approach on the important practical application of video shot cut detection.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
Kittler, J
Yusoff, Y
Windeatt, T
Date : 2001
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 11:38
Last Modified : 19 Dec 2019 00:29

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