Publications

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Book
Hassanien, A. E., Computational Intelligence in Biomedicine and Bioinformatics, , Germany, Studies in Computational Intelligence, Springer Vol. 151 , 2008. AbstractWebsite

The purpose of this book is to provide an overview of powerful state-of-the-art methodologies that are currently utilized for biomedicine and/ or bioinformatics-oriented applications, so that researchers working in those fields could learn of new methods to help them tackle their problems. On the other hand, the CI community will find this book useful by discovering a new and intriguing area of applications. In order to help fill the gap between the scientists on both sides of this spectrum, the editors have solicited contributions from researchers actively applying computational intelligence techniques to important problems in biomedicine and bioinformatics.

Hassanien, A. E., Computational Intelligence in Medical Imaging: Techniques and Applications, , USA, Chapman and Hall/CRC , 2009. AbstractWebsite

A compilation of the latest trends in the field, Computational Intelligence in Medical Imaging: Techniques and Applications explores how intelligent computing can bring enormous benefit to existing technology in medical image processing as well as improve medical imaging research. The contributors also cover state-of-the-art research toward integrating medical image processing with artificial intelligence and machine learning approaches.

Hassanien, A. E., Computational Intelligence in Multimedia Processing: Recent Advances, , USA, Studies in Computational Intelligence, Springer Vol. 96 , 2008. AbstractWebsite

For the last decades Multimedia processing has emerged as an important technology to generate content based on images, video, audio, graphics, and text. Furthermore, the recent new development represented by High Definition Multimedia content and Interactive television will generate a huge volume of data and important computing problems connected with the creation, processing and management of Multimedia content. "Computational Intelligence in Multimedia Processing: Recent Advances" is a compilation of the latest trends and developments in the field of computational intelligence in multimedia processing. This edited book presents a large number of interesting applications to intelligent multimedia processing of various Computational Intelligence techniques, such as rough sets, Neural Networks; Fuzzy Logic; Evolutionary Computing; Artificial Immune Systems; Swarm Intelligence; Reinforcement Learning and evolutionary computation.

Hassanien, A. - E., Computational Social Networks Analysis, , London, Computer Communications and Networks Series - Springer, 2010. AbstractWebsite

Social networks provide a powerful abstraction of the structure and dynamics of diverse kinds of people or people-to-technology interaction. Web 2.0 has enabled a new generation of web-based communities, social networks, and folksonomies to facilitate collaboration among different communities. This unique text/reference compares and contrasts the ethological approach to social behavior in animals with web-based evidence of social interaction, perceptual learning, information granulation, the behavior of humans and affinities between web-based social networks. An international team of leading experts present the latest advances of various topics in intelligent-social-networks and illustrates how organizations can gain competitive advantages by applying the different emergent techniques in real-world scenarios. The work incorporates experience reports, survey articles, and intelligence techniques and theories with specific network technology problems.

Book Chapter
Peters, J. F., and S. K. Pal, "Cantor, fuzzy, near, and rough sets in image analysis", Rough fuzzy image analysis: Foundations and methodologies: CRC Press, pp. 1–1, 2010. Abstract
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Ayeldeen, H., O. Hegazy, and A. E. Hassanien, "Case selection strategy based on K-means clustering", Information Systems Design and Intelligent Applications: Springer India, pp. 385–394, 2015. Abstract
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Ayeldeen, H., O. Shaker, O. Hegazy, and A. E. Hassanien, "Case-Based Reasoning: A Knowledge Extraction Tool to Use", Information systems design and intelligent applications: Springer India, pp. 369–378, 2015. Abstract
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Awad, A. I., A. E. Hassanien, and H. M. Zawbaa, "A cattle identification approach using live captured muzzle print images", Advances in Security of Information and Communication Networks: Springer Berlin Heidelberg, pp. 143–152, 2013. Abstract
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Hassanien, A. E., and J. M. Ali, "Classification and Retrieval of Images from Databases Using Rough Set Theory", Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications: IGI Global, pp. 179–198, 2009. Abstract
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Hassanien, A. E., and J. M. Ali, "Classification and Retrieval of Images from Databases Using Rough Set Theory", Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications: IGI Global, pp. 179–198, 2009. Abstract
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Mahmood, M. A., N. El-Bendary, A. E. Hassanien, and H. A. Hefny, "Classification Approach Based on Rough Mereology", Recent Advances in Intelligent Informatics: Springer International Publishing, pp. 175–184, 2014. Abstract
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Aziz, A. S. A., M. M. Fouad, and A. E. Hassanien, "Cloud Computing Forensic Analysis: Trends and Challenges", Multimedia Forensics and Security: Springer International Publishing, pp. 3–23, 2017. Abstract
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Alnashar, H. S., M. A. Fattah, M. M. Mosbah, and A. E. Hassanien, "Cloud computing framework for solving virtual college educations: A case of egyptian virtual university", Information Systems Design and Intelligent Applications: Springer India, pp. 395–407, 2015. Abstract
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Hassanien, A. E., "Clustering Time Series Data: An Evolutionary Approach ", Foundations of Computational Intelligence, Volume 206, pp.193-207: Springer , 2008. Abstract

Time series clustering is an important topic, particularly for similarity search amongst long time series such as those arising in bioinformatics, in marketing research, software engineering and management. This chapter discusses the state-of-the-art methodology for some mining time series databases and presents a new evolutionary algorithm for times series clustering an input time series data set. The data mining methods presented include techniques for efficient segmentation, indexing, and clustering time series.

Chiş, M., S. Banerjee, and A. E. Hassanien, "Clustering time series data: an evolutionary approach", Foundations of Computational, IntelligenceVolume 6: Springer Berlin Heidelberg, pp. 193–207, 2009. Abstract
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Chiş, M., S. Banerjee, and A. E. Hassanien, "Clustering time series data: an evolutionary approach", Foundations of Computational, IntelligenceVolume 6: Springer Berlin Heidelberg, pp. 193–207, 2009. Abstract
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Mohamed Tahoun, Abd El Rahman Shabayek, R. Reulke, and A. E. Hassanien, "Co-registration of Satellite Images Based on Invariant Local Features", Intelligent Systems' 2014: Springer International Publishing, pp. 653–660, 2015. Abstract
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Abdelhameed Ibrahim, T. Horiuchi, S. Tominaga, and A. E. Hassanien, "Color Invariant Representation and Applications", Handbook of Research on Machine Learning Innovations and Trends: IGI Global, pp. 1041–1061, 2017. Abstract
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Hassan, E. A., A. I. Hafez, A. E. Hassanien, and A. A. Fahmy, "Community detection algorithm based on artificial fish swarm optimization", Intelligent Systems' 2014: Springer International Publishing, pp. 509–521, 2015. Abstract
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Chakraborty, S., S. Chatterjee, N. Dey, A. S. Ashour, and A. E. Hassanien, "Comparative Approach Between Singular Value Decomposition and Randomized Singular Value Decomposition-based Watermarking", Intelligent Techniques in Signal Processing for Multimedia Security: Springer International Publishing, pp. 133–149, 2017. Abstract
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Hassanien, A. - E., A. Abraham, J. Kacprzyk, and J. F. Peters, "Computational intelligence in multimedia processing: foundation and trends", Computational Intelligence in Multimedia Processing: Recent Advances: Springer Berlin Heidelberg, pp. 3–49, 2008. Abstract
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Hassanien, A. - E., A. Abraham, J. Kacprzyk, and J. F. Peters, "Computational intelligence in multimedia processing: foundation and trends", Computational Intelligence in Multimedia Processing: Recent Advances: Springer Berlin Heidelberg, pp. 3–49, 2008. Abstract
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Hassanien, A. - E., A. Abraham, J. Kacprzyk, and J. F. Peters, "Computational intelligence in multimedia processing: foundation and trends", Computational Intelligence in Multimedia Processing: Recent Advances: Springer Berlin Heidelberg, pp. 3–49, 2008. Abstract
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Hassanien, A. E., "Computational Intelligence in Solving Bioinformatics Problems: Reviews, Perspectives Computational Intelligence in Solving Bioinformatics Problems: Reviews, Perspectives, and Challenges", Computational Intelligence in Biomedicine and Bioinformatics , London, Studies in Computational Intelligence,Springer, Volume 151/2008, 3-47, 2008. Abstract

This chapter presents a broad overview of Computational Intelligence (CI) techniques including Artificial Neural Networks (ANN), Particle Swarm Optimization (PSO), Genetic Algorithms (GA), Fuzzy Sets (FS), and Rough Sets (RS). We review a number of applications of computational intelligence to problems in bioinformatics and computational biology, including gene expression, gene selection, cancer classification, protein function prediction, multiple sequence alignment, and DNA fragment assembly. We discuss some representative methods to provide inspiring examples to illustrate how CI could be applied to solve bioinformatic problems and how bioinformatics could be analyzed, processed, and characterized by computational intelligence. Challenges to be addressed and future directions of research are presented. An extensive bibliography is also included.

Hassanien, A. - E., M. G. Milanova, T. G. Smolinski, and A. Abraham, "Computational intelligence in solving bioinformatics problems: Reviews, perspectives, and challenges", Computational Intelligence in Biomedicine and Bioinformatics: Springer Berlin Heidelberg, pp. 3–47, 2008. Abstract
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