Publications

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1998
Hasnine, A. E. H. H. K., and A. M. NAKAJIMA, Generation of Missing Mcdical Slices Using Morphing Technology, , 1998. Abstract
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Hassanien, A. E., H. Karam, H. Akter, and M. Nakajima:, "Generation of Missing Medical Slices Using Morphing Technology", Proceedings of IAPR Workshop on Machine Vision Applications, MVA 1998,, Chiba, Japan, November 17-19, 1998.
1999
Karam, H., A. - E. Hassanien, and M. Nakajima, "Graph grammar algebraic approach for generating fractal patterns", WSCG99 Inter. Conf., Czech Republic, pp. 492–500, 1999. Abstract
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2000
Haque, H., A. - E. Hassanien, and M. Nakajima, "Generation of missing medical slices using morphing technology", IEICE TRANSACTIONS on Information and Systems, vol. 83, no. 7: The Institute of Electronics, Information and Communication Engineers, pp. 1400–1407, 2000. Abstract
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Haque, H., A. - E. Hassanien, and M. Nakajima, "Generation of missing medical slices using morphing technology", IEICE TRANSACTIONS on Information and Systems, vol. 83, no. 7: The Institute of Electronics, Information and Communication Engineers, pp. 1400–1407, 2000. Abstract
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2008
El-Hosseini, M. A., A. E. Hassanien, A. Abraham, and H. Al-Qaheri, "Genetic annealing optimization: Design and real world applications", Intelligent Systems Design and Applications, 2008. ISDA'08. Eighth International Conference on, vol. 1: IEEE, pp. 183–188, 2008. Abstract
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El-Hosseini, M. A., A. E. Hassanien, A. Abraham, and H. Al-Qaheri, "Genetic annealing optimization: Design and real world applications", Intelligent Systems Design and Applications, 2008. ISDA'08. Eighth International Conference on, vol. 1: IEEE, pp. 183–188, 2008. Abstract
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2009
Al-Qaheri, H., A. E. Hassanien, and A. Abraham, "A Generic Scheme for Generating Prediction Rules Using Rough Sets", Rough Set Theory: A True Landmark in Data Analysis: Springer Berlin Heidelberg, pp. 163–186, 2009. Abstract
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Al-Qaheri, H., A. E. Hassanien, and A. Abraham, "A Generic Scheme for Generating Prediction Rules Using Rough Sets", Rough Set Theory: A True Landmark in Data Analysis: Springer Berlin Heidelberg, pp. 163–186, 2009. Abstract
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El Emary, I., and A. - E. Hassanien, "Guest editorial special issue on intelligent multimedia computing", Telecommunication Systems, vol. 40, no. 1: Springer, pp. 1–4, 2009. Abstract
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El Emary, I., and A. - E. Hassanien, "Guest editorial special issue on intelligent multimedia computing", Telecommunication Systems, vol. 40, no. 1: Springer, pp. 1–4, 2009. Abstract
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2012
Wahid, R., N. I. Ghali, H. S. Own, T. - H. Kim, and A. E. Hassanien, "A Gaussian mixture models approach to human heart signal verification using different feature extraction algorithms", Computer Applications for Bio-technology, Multimedia, and Ubiquitous City: Springer Berlin Heidelberg, pp. 16–24, 2012. Abstract
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Wahid, R., N. I. Ghali, H. S. Own, T. - H. Kim, and A. E. Hassanien, "A Gaussian mixture models approach to human heart signal verification using different feature extraction algorithms", Computer Applications for Bio-technology, Multimedia, and Ubiquitous City: Springer Berlin Heidelberg, pp. 16–24, 2012. Abstract
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Hafez, A. I., N. I. Ghali, A. E. Hassanien, and A. A. Fahmy, "Genetic algorithms for community detection in social networks", Intelligent Systems Design and Applications (ISDA), 2012 12th International Conference on: IEEE, pp. 460–465, 2012. Abstract
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Hafez, A. I., N. I. Ghali, A. E. Hassanien, and A. A. Fahmy, "Genetic algorithms for community detection in social networks", Intelligent Systems Design and Applications (ISDA), 2012 12th International Conference on: IEEE, pp. 460–465, 2012. Abstract
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Elmasry, W. H., H. M. Moftah, N. El-Bendary, and A. E. Hassanien, "Graph partitioning based automatic segmentation approach for ct scan liver images", Computer Science and Information Systems (FedCSIS), 2012 Federated Conference on: IEEE, pp. 183–186, 2012. Abstract
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Elmasry, W. H., H. M. Moftah, N. El-Bendary, and A. E. Hassanien, "Graph partitioning based automatic segmentation approach for ct scan liver images", Computer Science and Information Systems (FedCSIS), 2012 Federated Conference on: IEEE, pp. 183–186, 2012. Abstract
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Elmasry, W. H., H. M. Moftah, N. El-Bendary, and A. E. Hassanien, "Graph Partitioning based Automatic Segmentation Approach for CT Scan Liver Images", IEEE Federated Conference on Computer Science and Information Systems, pp. 205–208, Wroclaw - Poland , 9-13 Sept, 2012. Abstractgraph_partitioning_based_automatic_segmentation.pdf

Manual segmentation of liver computerized tomography (CT) images is very time consuming, so it is desired to develop a computer-based approach for the analysis of liver
CT images that can precisely segment the liver without any human intervention. This paper presents normalized cuts graph partitioning approach for liver segmentation from CT images. To evaluate the performance of the presented approach, we present tests on different liver CT images. Experimental results obtained show that the overall accuracy offered by the employed normalized cuts technique is high compared to the well known K-means segmentation approach.

Ahmed Ibrahim Hafez, N. Ghali, A. E. Hassanien, and A. Fahmy, "Genetic Algorithms for Multi-Objective Community Detection in Complex Networks ", IEEE International Conference on Intelligent Systems Design and Applications (ISDA) , Kochi, India, pp. 460 - 465, Nov. 27-29 2012. Abstract

Community detection in complex networks has attracted a lot of attention in recent years. Community detection can be viewed as an optimization problem, in which an objective function that captures the intuition of a community as a group of nodes with better internal connectivity than external connectivity is chosen to be optimized. Many single-objective optimization techniques have been used to solve the problem however those approaches have its drawbacks since they try optimizing one objective function and this results to a solution with a particular community structure property. More recently researchers viewed the problem as a multi-objective optimization problem and many approaches have been proposed to solve it. However which objective functions could be used with each other is still under debated since many objective functions have been proposed over the past years and in somehow most of them are similar in definition. In this paper we use Genetic Algorithm (GA) as an effective optimization technique to solve the community detection problem as a single-objective and multi-objective problem, we use the most popular objectives proposed over the past years, and we show how those objective correlate with each other, and their performances when they are used in the single-objective Genetic Algorithm and the Multi-Objective Genetic Algorithm and the community structure properties they tend to produce.

2013
Aziz, A. S. A., A. T. Azar, M. A. Salama, A. E. Hassanien, and S. E. - O. Hanafy, "Genetic algorithm with different feature selection techniques for anomaly detectors generation", Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on: IEEE, pp. 769–774, 2013. Abstract
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2014
Fattah, M. A., N. Elbendary, H. K. Elminir, M. A. A. El-Soud, and A. E. Hassanien, "Galaxies image classification using empirical mode decomposition and machine learning techniques", Engineering and Technology (ICET), 2014 International Conference on: IEEE, pp. 1–5, 2014. Abstract
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Hafez, A. I., E. T. Al-Shammari, A. E. Hassanien, and A. A. Fahmy, "Genetic algorithms for multi-objective community detection in complex networks", Social Networks: A Framework of Computational Intelligence: Springer International Publishing, pp. 145–171, 2014. Abstract
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Hafez, A. I., E. T. Al-Shammari, A. E. Hassanien, and A. A. Fahmy, "Genetic algorithms for multi-objective community detection in complex networks", Social Networks: A Framework of Computational Intelligence: Springer International Publishing, pp. 145–171, 2014. Abstract
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Hafez, A. I., E. T. Al-Shammari, A. E. Hassanien, and A. A. Fahmy:, "Genetic Algorithms for Multi-Objective Community Detection in Complex Networks.", Social Networks: A Framework of Computational Intelligence , London, Volume 526, pp 145-171, Springer, 2014.
Fattah, M. A., N. Elbendary, H. K. Elminir, M. A. A. El-Soud, and A. E. Hassanien, "Galaxies image classification using empirical mode decomposition and machine learning techniques ", The second International Conference on Engineering and Technology (ICET 2014) , German Uni - Cairo Egypt, 19 Apr - 20 Apr , 2014.
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