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Engineering Optimization Volume 44, 2012 - Issue 3: MULTI-OBJECTIVE METAHEURISTICS FOR MULTI-DISCIPLINARY ENGINEERING APPLICATIONS
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Original Articles

Adaptive multi-objective archive-based hybrid scatter search for segmentation in lung computed tomography imaging

Chin Wei Bong MIMOS Berhad, Technology Park Malaysia, Kuala Lumpur, Malaysia; School of Computer Science, Universiti Sains Malaysia, Penang, MalaysiaCorrespondence[email protected]
,
Hong Yoong Lam Ministry of Health, Department of Cardiothoracic Surgery, Hospital Penang, Malaysia
,
Ahamad Tajudin Khader School of Computer Science, Universiti Sains Malaysia, Penang, Malaysia
&
Hamzah Kamarulzaman Ministry of Health, Department of Cardiothoracic Surgery, Hospital Penang, Malaysia
Pages 327-350 | Received 28 Jan 2011, Accepted 10 Oct 2011, Published online: 27 Feb 2012

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Martin Marek & Petr Kadlec. (2022) Another evolution of generalized differential evolution: variable number of dimensions. Engineering Optimization 54:1, pages 61-80.
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Qichang Qiang, Baojun Lin, Yingchun Liu & Xia Lin. Prior information-based ellipse fitting optimization method for optical navigation with a short-arc horizon. Engineering Optimization 0:0, pages 1-17.
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Articles from other publishers (5)

A. D. López-SánchezJ. Sánchez-OroM. Laguna. (2020) A New Scatter Search Design for Multiobjective Combinatorial Optimization with an Application to Facility Location. INFORMS Journal on Computing.
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Benita K. J. Veronica. (2020) An effective neural network model for lung nodule detection in CT images with optimal fuzzy model. Multimedia Tools and Applications 79:19-20, pages 14291-14311.
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Nilanjan Dey & Amira S. Ashour. 2018. Advancements in Applied Metaheuristic Computing. Advancements in Applied Metaheuristic Computing 185 203 .
Nilanjan Dey & Amira S. Ashour. 2018. Soft Computing Based Medical Image Analysis. Soft Computing Based Medical Image Analysis 3 11 .
C.W. Bong, C.C. Liew & H.Y. Lam. 2016. Bio-Inspired Computation and Applications in Image Processing. Bio-Inspired Computation and Applications in Image Processing 87 104 .

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