Publications

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2012
Elmasry, W. H., H. M. Moftah, N. El-Bendary, and A. E. Hassanien, "Performance evaluation of computed tomography liver image segmentation approaches", Hybrid Intelligent Systems (HIS), 2012 12th International Conference on: IEEE, pp. 109–114, 2012. Abstract
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2013
Youssef, A., A. Nitaj, and A. E. Hassanien, Progress in Cryptology-AFRICACRYPT 2013, : Springer Berlin Heidelberg, 2013. Abstract
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Al-Shammari, E. T., A. E. Hassanien, and O. S. Al-Razgan, "Protecting Patient Privacy against Unauthorized Release of Medical Images Using Weighted Quantum Particle Swarm Optimization Algorithm", Pattern Recognition (ACPR), 2013 2nd IAPR Asian Conference on: IEEE, pp. 667–671, 2013. Abstract
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Yi Zhou, K. Xiao, Y. Wang, Alei Liang, and A. E. Hassanien, "A pso-inspired multi-robot map exploration algorithm using frontier-based strategy", International Journal of System Dynamics Applications (IJSDA), vol. 2, no. 2: IGI Global, pp. 1–13, 2013. Abstract
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Yi Zhou, K. Xiao, Y. Wang, Alei Liang, and A. E. Hassanien, "A pso-inspired multi-robot map exploration algorithm using frontier-based strategy", International Journal of System Dynamics Applications (IJSDA), vol. 2, no. 2: IGI Global, pp. 1–13, 2013. Abstract
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Mohamed Abd. Elfattah, N. El-Bendary, M. A. A. Elsoud, Jan Platoš, and A. E. Hassanien, "Principal Component Analysis Neural Network Hybrid Classification Approach for Galaxies Images.", Innovations in Bio-inspired Computing and Applications. Advances in Intelligent Systems and Computing(Springer) , Czech republic , 2013.
Yi Zhou, K. Xiao, Y. Wang, Alei Liang, and A. E. Hassanien, "A PSO-inspired Multi-Robot Map Exploration Algorithm Using Frontier-Based Strategy", International Journal of System Dynamics Applications,, vol. 2, issue 2, pp. 1-13, 2013. AbstractWebsite

Map exploration is a fundamental problem in mobile robots. This paper presents a distributed algorithm that coordinates a team of autonomous mobile robots to explore an unknown environment. The proposed strategy is based on frontiers which are the regions on the boundary between open and unexplored space. With this strategy, robots are guided to move constantly to the nearest frontier to reduce the size of unknown region. Based on the PSO model incorporated in the algorithm, robots are navigated towards remote frontier after exploring the local area. The exploration completes when there is no frontier cell in the environment. The experiments implemented on both simulated and real robot scenarios show that the proposed algorithm is capable of completing the exploration task. Compared to the conventional method of randomly selecting frontier, the proposed algorithm proves its efficiency by the decreased 60% exploration time at least. Additional experimental results show the decreased coverage time when the number of robots increases, which further suggests the validity, efficiency and scalability.

Al-Shammari, E. T., A. E. Hassanien, and O. Saleh, "Protecting Patient Privacy against Unauthorized Release of Medical Images Using Weighted Quantum Particle Swarm Optimization Algorithm", 2nd IAPR Asian Conference on Pattern Recognition (ACPR), pp 667- 671, Okinawa, Japan, 2013.
2014
Esraa Elhariri, N. El-Bendary, and A. E. Hassanien, "Plant classification system based on leaf features", Computer Engineering & Systems (ICCES), 2014 9th International Conference on: IEEE, pp. 271–276, 2014. Abstract
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El-Atta, A. A. H., M. I. Moussa, and A. E. Hassanien, "Predicting Biological Activity of 2, 4, 6-trisubstituted 1, 3, 5-triazines Using Random Forest", Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014: Springer International Publishing, pp. 101–110, 2014. Abstract
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Fattah, M. A., N. El-Bendary, M. A. A. Elsoud, Jan Platoš, and A. E. Hassanien, "Principal component analysis neural network hybrid Classification Approach for Galaxies Images", Innovations in Bio-inspired Computing and Applications: Springer International Publishing, pp. 225–237, 2014. Abstract
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Reham Gharbia, Ali Hassan El Baz, A. T. Azar, and A. E. Hassanien, "Principal component analysis and fuzzy-based rules approach for satellite image fusion", The annual IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Beijing, China, 6 July, 2014.
Emary, E., H. M. Zawbaa, and A. E. Hassanien, "Possibilistic fuzzy c-means clustering optimized with Cuckoo search for retinal vessel segmentation", The annual IEEE International Joint Conference on Neural Networks (IJCNN) –, Beijing, China, July 6-11, , 2014. Abstract

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Abder-Rahman Ali, Micael S. Couceiro, and A. E. Hassenian, "PSilhOuette: Towards an Optimal Number of Clusters using a Nested Particle Swarm Approach for Liver CT Image Segmentation ", The 2nd International Conference on Advanced Machine Learning Technologies and Applications , Egypt, November 17-19, , 2014.
2015
Gaber, T., Alaa Tharwat, V. Snasel, and A. E. Hassanien, "Plant identification: Two dimensional-based vs. one dimensional-based feature extraction methods", 10th international conference on soft computing models in industrial and environmental applications: Springer International Publishing, pp. 375–385, 2015. Abstract
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El-Atta, A. A. H., M. I. Moussa, and A. E. Hassanien, "Predicting activity approach based on new atoms similarity kernel function", Journal of Molecular Graphics and Modelling, vol. 60: Elsevier, pp. 55–62, 2015. Abstract
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Yakoub, F., Moustafa Zein, K. Yasser, A. Adl, and A. E. Hassanien, "Predicting personality traits and social context based on mining the smartphones SMS data", Intelligent Data Analysis and Applications: Springer International Publishing, pp. 511–521, 2015. Abstract
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El-Atta, A. A. H., M. I. Moussa, and A. E. Hassanien, "Predicting activity approach based on new atoms similarity kernel function", Journal of Molecular Graphics and Modelling, vol. 60, pp. 55–62, 2015. Website
Fatma Yakoub, Moustafa Zein, K. Y. A. A. A. E. H., "Predicting Personality Traits and Social Context Based on Mining the Smartphones SMS Data", Proceedings of the Second Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2015, , Ostrava, Czech Republic, , June 29 - July , 2015. Abstract

Reality Mining is one of the first efforts that have been exerted to utilize smartphone’s data; to analyze human behavior. The smartphone data are used to identify human behavior and discover more attributes about smartphone users, such as their personality traits and their relationship status. Text messages and SMS logs are two of the main data resources from the smartphones. In this paper, The proposed system define the user personality by observing behavioral characteristics derived from smartphone logs and the language used in text messages. Hence, The supervised machine learning methods (K-nearest nighbor (KNN), support vector machine, and Naive Bayes) and text mining techniques are used in studying the textual matter messages. From this study, The correlation between text messages and predicate users personality traits is broken down. The results provided an overview on how text messages and smartphone logs represent the user behavior; as they chew over the user personality traits with accuracy up to 70 %.

Tarek Gaber, Alaa Tharwat, V. S. A. E. H.:, "Plant Identification: Two Dimensional-Based Vs. One Dimensional-Based Feature Extraction Methods", 10th International Conference on Soft Computing Models in Industrial and Environmental Applications, Spain, july, 2015. Abstract

In this paper, a plant identification approach using 2D digital leaves images is proposed. The approach made use of two methods of features extraction (one-dimensional (1D) and two-dimensional (2D) techniques) and the Bagging classifier. For the 1D-based method, PCA and LDA techniques were applied, while 2D-PCA and 2D-LDA algorithms were used for the 2D-based method. To classify the extracted features in both methods, the Bagging classifier, with the decision tree as a weak learner, was used. The proposed approach, with its four feature extraction techniques, was tested using Flavia dataset which consists of 1907 colored leaves images. The experimental results showed that the accuracy and the performance of our approach, with the 2D-PCA and 2D-LDA, was much better than using the PCA and LDA. Furthermore, it was proven that the 2D-LDA-based method gave the best plant identification accuracy and increasing the weak learners of the Bagging classifier leaded to a better accuracy. Also, a comparison with the most related work showed that our approach achieved better accuracy under the same dataset and same experimental setup.

2016
Abder-Rahman Ali, Micael Couceiro, A. Anter, and A. - E. Hassanien, "Particle swarm optimization based fast fuzzy C-means clustering for liver CT segmentation", Applications of Intelligent Optimization in Biology and Medicine: Springer International Publishing, pp. 233–250, 2016. Abstract
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Sahlol, A., M. A. Fattah, C. Y. Suen, and A. E. Hassanien, "Particle Swarm Optimization with Random Forests for Handwritten Arabic Recognition System", International Conference on Advanced Intelligent Systems and Informatics: Springer International Publishing, pp. 437–446, 2016. Abstract
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Azar, A. T., S. S. Kumar, H. H. Inbarani, and A. E. Hassanien, "Pessimistic multi-granulation rough set-based classification for heart valve disease diagnosis", International Journal of Modelling, Identification and Control, vol. 26, no. 1: Inderscience Publishers (IEL), pp. 42–51, 2016. Abstract
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Alaa Tharwat, Hani Mahdi, and A. E. Hassanien, "Plant Recommender System Based on Multi-label Classification", International Conference on Advanced Intelligent Systems and Informatics: Springer International Publishing, pp. 825–835, 2016. Abstract
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Tourism