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Zawbaa, H. M., N. El-Bendary, A. E. Hassanien, and V. Snasel, "Semi-automatic annotation system for home videos", Intelligent Systems Design and Applications (ISDA), 2010 10th International Conference on: IEEE, pp. 1275–1280, 2010. Abstract
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Zawbaa, H. M., N. El-Bendary, A. E. Hassanien, and A. Abraham, "SVM-based soccer video summarization system", Nature and Biologically Inspired Computing (NaBIC), 2011 Third World Congress on: IEEE, pp. 7–11, 2011. Abstract
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Zawbaa, H. M., N. El-Bendary, A. E. Hassanien, and A. Abraham, "SVM-based soccer video summarization system", Nature and Biologically Inspired Computing (NaBIC), 2011 Third World Congress on: IEEE, pp. 7–11, 2011. Abstract
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Zawbaa, H. M., N. El-Bendary, A. E. Hassanien, G. Schaefer, and S. - S. Yeo, "Support Vector Machine based Logo Detection in Broadcast Soccer Videos", The 16th Online World Conference on Soft Computing in Industrial Applications (WSC16) Advances in Intelligent and Soft Computing, , 5-6 Dec, 2011. Abstract

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Salama, M., M. Panda, Y. Elbarawy, A. E. Hassanien, and A. Abraham, "Social Networks Security and Privacy: Basics,Threats and Case Study to Visualize Foreign Terrorist Network dataset", Computational Social Networks: Security and Privacy, London, Series in Computer Communications and Networks, Springer Verlag, , 2012. Abstract

The continuous self-growing nature of social networks makes it hard to define a line of safety around these networks. Users in social networks are not interacting with the web only, but also with trusted groups that may contain enemies. There are different kinds of attacks on these networks including causing damage to the computer systems and steeling information about users. These attacks are not affecting individuals only, but also the organizations they are belonging to. Protection from these attacks should be performed by the users and security experts of the network. Advices should be provided to users of these social networks. Also security-experts should be sure that the contents transmitted through the network do not contain malicious or harmful data. This chapter shows the security risks and the tasks applied to minimize those risks. Explain the most famous ways that attackers and malicious use. Then show the security measures for each way. Also present a security guide and a social network security and privacy made in 2011, and finally a case study about the list of Foreign Terrorist Network dataset.

Saad, O., A. Darwish, and R. Faraj, "A survey of machine learning techniques for Spam filtering", International Journal of Computer Science and Network Security (IJCSNS), vol. 12, no. 2: International Journal of Computer Science and Network Security, pp. 66, 2012. Abstract
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Reham Gharbia, and A. E. Hassanien, "Swarm Intelligence Based on Remote Sensing Image Fusion: Comparison between the Particle Swarm Optimization and the Flower Pollination Algorithm ", Handbook of Research on Machine Learning Innovations and Trends, USA, IGI, 2017. Abstract

This chapter presents a remote sensing image fusion based on swarm intelligence. Image fusion is combining multi-sensor images in a single image that has most informative. Remote sensing image fusion is an effective way to extract a large volume of data from multisource images. However, traditional image fusion approaches cannot meet the requirements of applications because they can lose spatial information or distort spectral characteristics. The core of the image fusion is image fusion rules. The main challenge is getting suitable weight of fusion rule. This chapter proposes swarm intelligence to optimize the image fusion rule. Swarm intelligence algorithms are a family of global optimizers inspired by swarm phenomena in nature and have shown better performance. In this chapter, two remote sensing image fusion based on swarm intelligence algorithms, Particle Swarm Optimization (PSO) and flower pollination algorithm are presented to get an adaptive image fusion rule and comparative between them.

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Panda, M., N. El-Bendary, M. Salama, A. E. Hassanien, and A. Abraham, "Social Networks Analysis: Basics, Measures and Visualizing Authorship Networks in DBLP Data", Computational Social Networks: Mining and Visualization, London, Series in Computer Communications and Networks, Springer Verlag, 2012. Abstract

Social Network Analysis (SNA) is becoming an important tool for investigators, but all the necessary information is often available in a distributed environment. Currently there is no information system that helps managers and team leaders to monitor the status of a social network. This chapter presents an overview of the basic concepts of social networks in data analysis including social networks analysis metrics and performances. Different problems in social networks are discussed such as uncertainty, missing data and finding the shortest path in social network. Community structure, detection and visualization in social network analysis is also discussed and reviewed. This chapter bridges the gap among the users by combining social network analysis methods and information visualization technology to help user visually identify the occurrence of a possible relationship amongst the members in a social network. In addition, briefly describing the different performance measures that have been encountered during any network analysis in order to understand the fundamental behind the comprehension. This chapter also, presents an online analysis tool called Forcoa.NET, which is built over the DBLP dataset of publications from the field of computer science, which is focused on the analysis and visualization of the co-authorship relationship based on the intensity and topic of joint publications. Challenges to be ad dressed and future directions of research are also presented and an extensive bibliography is included.order to understand the fundamental behind the comprehension. This chapter also, presents an online analysis tool called Forcoa.NET, which is built over the DBLP dataset of publications from the field of computer science, which is focused on the analysis and visualization of the co-authorship relationship based on the intensity and topic of joint publications. Challenges to be ad dressed and future directions of research are also presented and an extensive bibliography is included.

M
Moustafa Zein, A. Adl, A. E. Hassanien, A. Badr, and T. - H. Kim, "A Social Relationship Modifiers Modeller", Computer, Information and Application (CIA), 2015 3rd International Conference on: IEEE, pp. 33–37, 2015. Abstract
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Mohamed Tahoun, Abd El Rahman Shabayek, H. Nassar, M. M. Giovenco, R. Reulke, Eid Emary, and A. E. Hassanien, "Satellite Image Matching and Registration: A Comparative Study Using Invariant Local Features", Image Feature Detectors and Descriptors: Springer International Publishing, pp. 135–171, 2016. Abstract
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Mahmoud, R., N. El-Bendary, H. M. O. Mokhtar, and A. E. Hassanien, "Similarity Measures based Recommender System for Rehabilitation of People with Disabilities", the 1st International Conference on Advanced Intelligent Systems and Informatics (AISI’15) Springer, Beni Suef University, Beni Suef, Eg, Nov. 28-30, 2015. Abstract

This paper proposes a recommender system to predict and suggest a
set of rehabilitation methods for patients with spinal cord injuries (SCI). The proposed
system automates, stores and monitors the heath conditions of SCI patients.
The International Classification of Functioning, Disability and Health classification
(ICF) is used to stores and monitors the progress in health status. A set of
similarity measures are utilized in order to get the similarity between patients and
predict the rehabilitation recommendations. Experimental results showed that the
proposed recommender system has obtained an accuracy of 98% via implementing
the cosine similarity measure.

Mahmoud, R., N. El-Bendary, H. M. O. Mokhtar, and A. E. Hassanien, "Similarity Measures Based Recommender System for Rehabilitation of People with Disabilities", The 1st International Conference on Advanced Intelligent System and Informatics (AISI2015), November 28-30, 2015, Beni Suef, Egypt: Springer International Publishing, pp. 523–533, 2016. Abstract
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Liu, H., A. Abraham, and A. E. Hassanien, "Scheduling jobs on computational grids using a fuzzy particle swarm optimization algorithm", Future Generation Computer Systems, vol. 26, no. 8: Elsevier, pp. 1336–1343, 2010. Abstract
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Liang Chen, S. Feng, W. Zhang, A. E. Hassanien, and H. Liu, "Sparse ICA based on Infinite Norm for fMRI Analysis ", The 2nd International Conference on Advanced Machine Learning Technologies and Applications , Egypt, November 17-19, , 2014.
Liang Chen, S. Feng, W. Zhang, A. E. Hassanien, and H. Liu, "Sparse ICA Based on Infinite Norm for fMRI Analysis", International Conference on Advanced Machine Learning Technologies and Applications: Springer International Publishing, pp. 379–388, 2014. Abstract
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K
Kotyk, T., S. Chakraborty, N. Dey, T. Gaber, A. E. Hassanien, and V. Snasel, "Semi-automated System for Cup to Disc Measurement for Diagnosing Glaucoma Using Classification Paradigm", Proceedings of the Second International Afro-European Conference for Industrial Advancement AECIA 2015: Springer International Publishing, pp. 653–663, 2016. Abstract
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KAMAL, K. A. R. E. E. M., A. GHANY, M. A. Moneim, N. I. Ghali, A. E. Hassanien, and H. A. Hefny, A symmetric bio-hash function based on fingerprint minutiae and principal curves approach, , 2011. Abstract
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KAMAL, K. A. R. E. E. M., A. GHANY, M. A. Moneim, N. I. Ghali, A. E. Hassanien, and H. A. Hefny, A symmetric bio-hash function based on fingerprint minutiae and principal curves approach, , 2011. Abstract
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Inbarani, H. H., S. S. Kumar, A. T. Azar, and A. E. Hassanien, "Soft rough sets for heart valve disease diagnosis", International Conference on Advanced Machine Learning Technologies and Applications: Springer International Publishing, pp. 347–356, 2014. Abstract
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Hassanien, A., M. Nachtegael, D. VAN DER WEKEN, H. NOBUHARA, and E. Kerre, Soft Computing in Image Processing, : Springer, 2006. Abstract
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Hassanien, A. E., A. Abraham, and C. Grosan, "Spiking neural network and wavelets for hiding iris data in digital images", Soft Computing-A Fusion of Foundations, Methodologies and Applications, vol. 13, no. 4: Springer Berlin/Heidelberg, pp. 401–416, 2009. Abstract
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Hassanien, A. E., and Eid Emary, Swarm intelligence: principles, advances, and applications, : CRC Press, 2016. Abstract
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Hassanien, A. E., H. Takahashi, and M. Nakajima, "Semiautomatic feature specification based on snakes for image morphing", Optical Science, Engineering and Instrumentation'97: International Society for Optics and Photonics, pp. 494–502, 1997. Abstract
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Hassanien, A., M. Nachtegael, D. VAN DER WEKEN, H. NOBUHARA, and E. Kerre, Soft Computing in Image Processing, : Springer, 2006. Abstract
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Tourism