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Self-adaptation of mutation operator and probability for permutation representations in genetic algorithms (2010)
Journal Article
Serpell, M., & Smith, J. (2010). Self-adaptation of mutation operator and probability for permutation representations in genetic algorithms. Evolutionary Computation, 18(3), 491-514. https://doi.org/10.1162/EVCO_a_00006

The choice of mutation rate is a vital factor in the success of any genetic algorithm (GA), and for permutation representations this is compounded by the availability of several alternative mutation operators. It is now well understood that there is... Read More about Self-adaptation of mutation operator and probability for permutation representations in genetic algorithms.

Assessment of the influence of adaptive components in trainable surface inspection systems (2010)
Journal Article
Van Brussel, H., Eitzinger, C., Heidl, W., Lughofer, E., Raiser, S., Smith, J., …Sannen, D. (2010). Assessment of the influence of adaptive components in trainable surface inspection systems. Machine Vision and Applications, 21(5), 613-626. https://doi.org/10.1007/s00138-009-0211-1

In this paper, we present a framework for the classification of images in surface inspection tasks and address several key aspects of the processing chain from the original image to the final classification result. A major contribution of this paper... Read More about Assessment of the influence of adaptive components in trainable surface inspection systems.

Impact of object extraction methods on classification performance in surface inspection systems (2010)
Journal Article
Raiser, S., Lughofer, E., Eitzinger, C., & Smith, J. (2010). Impact of object extraction methods on classification performance in surface inspection systems. Machine Vision and Applications, 21(5), 627-641. https://doi.org/10.1007/s00138-009-0205-z

In surface inspection applications, the main goal is to detect all areas which might contain defects or unacceptable imperfections, and to classify either every single 'suspicious' region or the investigated part as a whole. After an image is acquire... Read More about Impact of object extraction methods on classification performance in surface inspection systems.

Creating diverse nearest-neighbour ensembles using simultaneous metaheuristic feature selection (2010)
Journal Article
Tahir, M. A., & Smith, J. (2010). Creating diverse nearest-neighbour ensembles using simultaneous metaheuristic feature selection. Pattern Recognition Letters, 31(11), 1470-1480. https://doi.org/10.1016/j.patrec.2010.01.030

The nearest-neighbour (1NN) classifier has long been used in pattern recognition, exploratory data analysis, and data mining problems. A vital consideration in obtaining good results with this technique is the choice of distance function, and corresp... Read More about Creating diverse nearest-neighbour ensembles using simultaneous metaheuristic feature selection.

User-centric image segmentation using an interactive parameter adaptation tool (2010)
Journal Article
Pauplin, O., Caleb-Solly, P., & Smith, J. (2010). User-centric image segmentation using an interactive parameter adaptation tool. Pattern Recognition, 43(2), 519-529. https://doi.org/10.1016/j.patcog.2009.03.007

Creating successful machine vision systems often begins a process of developing customised reliable image segmentation algorithms for the detection, and possibly categorisation of regions of interest within images. This can require significant invest... Read More about User-centric image segmentation using an interactive parameter adaptation tool.

Human-machine interaction issues in quality control based on online image classification (2009)
Journal Article
Lughofer, E., Smith, J., Tahir, M. A., Caleb-Solly, P., Eitzinger, C., Sannen, D., & Nuttin, M. (2009). Human-machine interaction issues in quality control based on online image classification. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 39(5), 960-971. https://doi.org/10.1109/TSMCA.2009.2025025

This paper considers on a number of issues that arise when a trainable machine vision system learns directly from humans. We contrast this to the "normal" situation where machine learning (ML) techniques are applied to a "cleaned" data set which is c... Read More about Human-machine interaction issues in quality control based on online image classification.

Human-machine interaction issues in quality control based on on-line image classification (2009)
Journal Article
Lughofer, E., Smith, J., Tahir, M., Caleb-Solly, P., Eitzinger, C., Sannen, D., & Nuttin, M. (2009). Human-machine interaction issues in quality control based on on-line image classification. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 39(5), 960-971. https://doi.org/10.1109/TSMCA.2009.2025025

This paper considers on a number of issues that arise when a trainable machine vision system learns directly from humans. We contrast this to the ldquonormalrdquo situation where machine learning (ML) techniques are applied to a ldquocleanedrdquo dat... Read More about Human-machine interaction issues in quality control based on on-line image classification.

An on-line interactive self-adaptive image classification framework (2008)
Journal Article
Sannen, D., Nuttin, M., Smith, J., Tahir, M. A., Caleb-Solly, P., Lughofer, E., & Eitzinger, C. (2008). An on-line interactive self-adaptive image classification framework. Lecture Notes in Artificial Intelligence, 5008 LNCS, 171-180. https://doi.org/10.1007/978-3-540-79547-6_17

In this paper we present a novel image classification framework, which is able to automatically re-configure and adapt its feature-driven classifiers and improve its performance based on user interaction during on-line processing mode. Special emphas... Read More about An on-line interactive self-adaptive image classification framework.

Memetic algorithms: The polynomial local search complexity theory perspective (2008)
Journal Article
Krasnogor, N., & Smith, J. (2008). Memetic algorithms: The polynomial local search complexity theory perspective. Journal of Mathematical Modelling and Algorithms, 7(1), 3-24. https://doi.org/10.1007/s10852-007-9070-9

In previous work (Krasnogor, http://www.cs.nott.ac.uk/~nxk/papers.html . In: Studies on the Theory and Design Space of Memetic Algorithms. Ph.D. thesis, University of the West of England, Bristol, UK, 2002; Krasnogor and Smith, IEEE Trans Evol Algori... Read More about Memetic algorithms: The polynomial local search complexity theory perspective.

Computer vision applications - Special issue (2007)
Journal Article
Smith, L. N., Smith, M. L., Caleb-Solly, P., & Smith, J. (2007). Computer vision applications - Special issue. Image and Vision Computing, 25(7), 1035-1036. https://doi.org/10.1016/j.imavis.2007.04.001

This peer-reviewed international journal paper arose from a research collaboration which formed part of the PhD of a colleague and builds on previous conferences works [proceedings of "Adaptative Computing in Design and Manufacturing" 2002, 2005, pro... Read More about Computer vision applications - Special issue.

Parameter control in evolutionary algorithms (2007)
Journal Article
Eiben, A., Michalewicz, Z., Schoenauer, M., & Smith, J. (2007). Parameter control in evolutionary algorithms. Studies in Computational Intelligence, 54, 19-46. https://doi.org/10.1007/978-3-540-69432-8_2

The issue of setting the values of various parameters of an evolutionary algorithm is crucial for good performance. In this paper we discuss how to do this, beginning with the issue of whether these values are best set in advance or are best changed... Read More about Parameter control in evolutionary algorithms.

On replacement strategies in steady state evolutionary algorithms (2007)
Journal Article
Smith, J. (2007). On replacement strategies in steady state evolutionary algorithms. Evolutionary Computation, 15(1), 29-59. https://doi.org/10.1162/evco.2007.15.1.29

Steady State models of Evolutionary Algorithms are widely used, yet surprisingly little attention has been paid to the effects arising from different replacement strategies. This paper explores the use of mathematical models to characterise the selec... Read More about On replacement strategies in steady state evolutionary algorithms.

Coevolving memetic algorithms: A review and progress report (2007)
Journal Article
Smith, J. (2007). Coevolving memetic algorithms: A review and progress report. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 37(1), 6-17. https://doi.org/10.1109/TSMCB.2006.883273

Coevolving memetic algorithms are a family of metaheuristic search algorithms in which a rule-based representation of local search (LS) is coadapted alongside candidate solutions within a hybrid evolutionary system. Simple versions of these systems h... Read More about Coevolving memetic algorithms: A review and progress report.

A tutorial for competent memetic algorithms: Model, taxonomy and design issues (2005)
Journal Article
Krasnogor, N., & Smith, J. (2005). A tutorial for competent memetic algorithms: Model, taxonomy and design issues. IEEE Transactions on Evolutionary Computation, 9(5), 474-488. https://doi.org/10.1109/TEVC.2005.850260

The combination of evolutionary algorithms with local search was named "memetic algorithms" (MAs) (Moscato, 1989). These methods are inspired by models of natural systems that combine the evolutionary adaptation of a population with individual learni... Read More about A tutorial for competent memetic algorithms: Model, taxonomy and design issues.

A tutorial for competent memetic algorithms: Model, taxonomy, and design issues (2005)
Journal Article
Krasnogor, N., & Smith, J. (2005). A tutorial for competent memetic algorithms: Model, taxonomy, and design issues. IEEE Transactions on Evolutionary Computation, 9(5), 474-488. https://doi.org/10.1109/TEVC.2005.850260

The combination of evolutionary algorithms with local search was named "memetic algorithms" (MAs) (Moscato, 1989). These methods are inspired by models of natural systems that combine the evolutionary adaptation of a population with individual learni... Read More about A tutorial for competent memetic algorithms: Model, taxonomy, and design issues.