Journal Article10.1016/J.PATREC.2004.06.005
Synthesizing feature agents using evolutionary computation
Bir Bhanu,Yingqiang Lin +1 more
TL;DR: Compared to normal GP, the GP algorithm with smart crossover and smart mutation can find good agents more quickly during training to effectively extract the regions-of-interest and the learned agents can be applied to extract ROIs in other similar images.
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About: This article is published in Pattern Recognition Letters. The article was published on 01 Oct 2004. The article focuses on the topics: Genetic programming & Crossover.
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Citations
•Book
Evolutionary Synthesis of Pattern Recognition Systems
Bir Bhanu,Yingqiang Lin,Krzysztof Krawiec +2 more
- 17 Feb 2005
TL;DR: Feature Synthesis for Object Detection, Mdl-Based Efficient Genetic Programming for Object detection, and Applications of Linear Genetic programming for Object Recognition are described.
36
Evolutionary computer vision
Gustavo Olague
- 07 Jul 2007
TL;DR: Evolutionary Computer Vision (ECV) is a recent research area devoted to the study of artificial vision through evolutionary and genetic computing approaches.
14
Feature fusion of mechanical faults based on evolutionary computation
TL;DR: An evolutionary algorithm for mechanical fault recognition based on genetic programming (GP) and information fusion techniques is proposed that can generate composite feature vectors with more information about machine faults, which are used in automatic recognition of different mechanical faults without prior knowledge of the machine itself.
3
•Dissertation
Investigating evolutionary computation with smart mutation for three types of Economic Load Dispatch optimisation problem
Sunny Orike
- 01 Jan 2015
TL;DR: In this article, the Dynamic Economic Load Dispatch (DELD) problem is defined under the assumption of a regulated electricity market, where utilities tend to share their generating resources so as to minimise the total cost of supplying the demanded load.
1
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- 01 Jan 2004
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