Automated tracking approach with ant colonies for different cell population density distribution-Reference-Cited by-同舟云学术

Automated tracking approach with ant colonies for different cell population density distribution

Published:2016-02-10 Issue:14 Volume:21 Page:3977-3992
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Lu Mingli,Xu Benlian,Jiang Zhengqiang,Sheng Andong,Zhu Peiyi,Shi Jian

Funder

National Natural Science Foundation of China

the natural science fundamental research program of higher education colleges in Jiangsu province

Suzhou Municipal Science and Technology Plan Project

the project of talent peak of six industries

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

http://link.springer.com/article/10.1007/s00500-016-2048-7/fulltext.html

Reference34 articles.

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2. Ba-Ngu V, Wing-Kin M (2006) The gaussian mixture probability hypothesis density filter. IEEE Trans Signal Process 54:4091–4104

3. Bell JE, McMullen PR (2004) Ant colony optimization techniques for the vehicle routing problem. Adv Eng Inf 18:41–48

4. Blum C (2005) Beam-ACO-hybridizing ant colony optimization with beam search: an application to open shop scheduling. Comput Oper Res 32:1565–1591

5. Charles JB, Michael Halter H, Elliott J (2012) Evaluation of segmentation algorithms on cell populations using CDF curves.pdf. IEEE Trans Med Imag 31:11

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