A genetic programming framework in the automatic design of combination models for salient object detection-Reference-Cited by-同舟云学术

A genetic programming framework in the automatic design of combination models for salient object detection

Published:2019-03-05 Issue:3 Volume:20 Page:285-325
ISSN:1389-2576
Container-title:Genetic Programming and Evolvable Machines
language:en
Short-container-title:Genet Program Evolvable Mach

Author:

Contreras-Cruz Marco A.^ORCID,Martinez-Rodriguez Diana E.^ORCID,Hernandez-Belmonte Uriel H.^ORCID,Ayala-Ramirez Victor^ORCID

Funder

Consejo Nacional de Ciencia y Tecnología

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Hardware and Architecture,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s10710-019-09345-5.pdf

Reference89 articles.

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3. S. Afzali, B. Xue, H. Al-Sahaf, M. Zhang, A supervised feature weighting method for salient object detection using particle swarm optimization, in Computational Intelligence (SSCI), 2017 IEEE Symposium Series on (IEEE, 2017), pp. 1–8

4. H. Al-Sahaf, A. Al-Sahaf, B. Xue, M. Johnston, M. Zhang, Automatically evolving rotation-invariant texture image descriptors by genetic programming. IEEE Trans. Evolut. Comput. 21(1), 83–101 (2017)

5. H. Al-Sahaf, A. Song, K. Neshatian, M. Zhang, Two-tier genetic programming: towards raw pixel-based image classification. Expert Syst. Appl. 39(16), 12291–12301 (2012)

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