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Abdelsalam, M., M. A. Mahmood, Yasser Mahmoud Awad, M. Hazman, N. Elbendary, A. E. Hassanien, M. F. Tolba, and S. M. Saleh, "Climate recommender system for wheat cultivation in North Egyptian Sinai Peninsula", Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014: Springer International Publishing, pp. 121–130, 2014. Abstract
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Abdelsalam, M., Mahmood A. Mahmood, Yasser Mahmoud Awad, M. Hazman, N. Elbendary, A. E. Hassanien, M. F. Tolba, and S. M. Saleh, "Climate recommender system for wheat cultivation in North Egyptian Sinai Peninsula", The 5th International Conference on Innovations in Bio-Inspired Computing and Applications (Springer) IBICA2014, Ostrava, Czech Republic., 22-24 June, 2013.
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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Abdelhameed Ibrahim, ali ahmed, S. Hussein, and A. E. Hassanien, "Fish Image Segmentation Using Salp Swarm Algorithm", Download book PDF EPUB International Conference on Advanced Machine Learning Technologies and Applications, Cairo, 23 Feb, 2018. Abstract

Fish image segmentation can be considered an essential process in developing a system for fish recognition. This task is challenging as different specimens, rotations, positions, illuminations, and backgrounds exist in fish images. In this research, a segmentation model is proposed for fish images using Salp Swarm Algorithm (SSA). The segmentation is formulated using Simple Linear Iterative Clustering (SLIC) method with initial parameters optimized by the SSA. The SLIC method is used to cluster image pixels to generate compact and nearly uniform superpixels. Finally, a thresholding using Otsu’s method helped to produce satisfactory results of extracted fishes from the original images under different conditions. A fish dataset consisting of real-world images was tested. In experiments, the proposed model shows robustness for different cases compared to conventional work.

Abdelhameed Ibrahim, T. Gaber, T. Horiuchi, V. Snasel, and A. E. Hassanien, "Human Thermal Face Extraction Based on SuperPixel Technique", The 1st International Conference on Advanced Intelligent System and Informatics (AISI2015), November 28-30, 2015, Beni Suef, Egypt: Springer International Publishing, pp. 163–172, 2016. Abstract
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Abdelhameed Ibrahim, T. Horiuchi, S. Tominaga, and A. E. Hassanien, "Spectral Reflectance Images and Applications", Image Feature Detectors and Descriptors: Springer International Publishing, pp. 227–254, 2016. 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,, USA, IGI, USA, pp.21, 2017. Abstract

Illumination factors such as shading, shadow, and highlight observed from object surfaces affect the appearance and analysis of natural color images. Invariant representations to these factors were presented in several ways. Most of these methods used the standard dichromatic reflection model that assumed inhomogeneous dielectric material. The standard model cannot describe metallic objects. This chapter introduces an illumination-invariant representation that is derived from the standard dichromatic reflection model for inhomogeneous dielectric and the extended dichromatic reflection model for homogeneous metal. The illumination color is estimated from two inhomogeneous surfaces to recover the surface reflectance of object without using a reference white standard. The overall performance of the invariant representation is examined in experiments using real-world objects including metals and dielectrics in detail. The feasibility of the representation for effective edge detection is introduced and compared with the state-of-the-art illumination-invariant methods.

Abdelhameed Ibrahim, T. Gaber, T. Horiuchi, V. Snasel, and A. E. Hassanien, "Human Thermal Face Extraction Based on SuperPixel Technique ", the 1st International Conference on Advanced Intelligent Systems and Informatics (AISI’15) Springer. , Beni Suef University, Beni Suef, Egypt , Nov. 28-30, 2015. Abstract

Face extraction is considered a very important step in devel-
oping a recognition system. It is a challenging task as there are di erent
face expressions, rotations, and artifacts including glasses and hats. In
this paper, a face extraction model is proposed for thermal IR human face
images based on superpixel technique. Superpixels can improve the com-
putational eciency of algorithms as it reduces hundreds of thousands of
pixels to at most a few thousand superpixels. Superpixels in this paper
are formulated using the quick-shift method. The Quick-Shift's superpix-
els and automatic thresholding using a simple Otsu's thresholding help
to produce good results of extracting faces from the thermal images. To
evaluate our approach, 18 persons with 22,784 thermal images were used
from the Terravic Facial IR Database. The Experimental results showed
that the proposed model was robust against image illumination, face
rotations, and di erent artifacts in many cases compared to the most
related work.

Abdelaziz, A., A. Adl, Moustafa Zein, M. Atef, K. K. A. Ghany, and A. E. Hassanien, "An Orphan Drug Legislation System", IEEE Conf. on Intelligent Systems (2) 2014: 389-399, Poland - Warsaw , 24 -26 Sept. , 2014. Abstract

Orphan drugs are a treatment for rare diseases. From that, comes the importance of orphan drug development and discovery. For an orphan drug to be approved by the FDA, it does not have to be similar to any approved orphan drug. So chemists opinions are important to determine the probability of similarity. It is too hard to check all orphan drugs for any rare disease. It takes a long time and big effort, so we introduce in this study a system that classifies the orphan drugs according to their probability of structural similarity. It also compares between them and the unauthorized orphan drug to determine the closest orphan drug to it. That system helps chemists to study a certain orphan database using the five features. That system provides better results. It provides chemists with the clusters of orphan drugs after adding the drug that needs to be authorized to its cluster.

Abdelaziz, A., Moustafa Zein, M. Atef, A. Adl, K. K. A. Ghany, and A. E. Hassanien, "An Orphan Drug Legislation System", Intelligent Systems' 2014: Springer International Publishing, pp. 389–399, 2015. Abstract
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Abdelaziz, A., A. Adl, Moustafa Zein, M. Atef, K. K. A. Ghany, and A. E. Hassanien, "An Orphan Drug Legislation System", IEEE Conf. on Intelligent Systems (2) 2014: 389-399, 2014. Abstract

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Abdelazeem, M., Eid Emary, and A. E. Hassanien, "A hybrid Bat-regularized Kaczmarz algorithm to solve ill-posed geomagnetic inverse problem", The 1st International Conference on Advanced Intelligent System and Informatics (AISI2015), November 28-30, 2015, Beni Suef, Egypt: Springer International Publishing, pp. 263–272, 2016. Abstract
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Abdelazeem, M., E. Emary, and A. E. Hassanien, "A hybrid Bat-regularized Kaczmarz Algorithm to Solve Ill-posed Geomagnetic Inverse Problem", the 1st International Conference on Advanced Intelligent Systems and Informatics (AISI’15) Springer., Beni Suef University, Beni Suef, Eg, Nov. 28-30, 2015. Abstract

The aim of geophysical inverse problem is to determine the
spatial distribution and depths to buried targets at a variety of scales;
it ranges from few centimetres to many kilometres. To identify ore bodies,
extension of archaeological targets, old mines, unexploded ordnance
(UXO) and oil traps, the linear geomagnetic inverse problem resulted
from the Fredholm integral equation of the first kind is solved using
many strategies. The solution is usually affected by the condition of
the kernel matrix of the linear system and the noise level in the data
collected. In this paper, regularized Kaczmarz method is used to get a
regularized solution. This solution is taken as an initial solution to bat
swarm algorithm (BA) as a global swarm-based optimizer to refine the
quality and reach a plausible model. To test efficiency, the proposed hybrid
method is applied to different synthetic examples of different noise
levels and different dimensions and proved an advance over using the
Kaczmarz method.

Abdel-Aziz, A. S., A. E. Hassanien, A. T. Azar, and S. E. - O. Hanafi, "Machine learning techniques for anomalies detection and classification", Advances in security of information and communication networks: Springer Berlin Heidelberg, pp. 219–229, 2013. Abstract
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Abdalla Zidan, N. I. Ghali, A. Hassanien, H. Hefny, and J. Hemanth, "Level set-based CT liver computer aided diagnosis system", Int. J. Imaging Robot, vol. 9, pp. 26–36, 2013. Abstract
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Abdalla Zidan, N. Ghali, A. E. Hassanien, and H. Hefny, "Level Set-based CT Liver Image Segmentation with Watershed and Artificial Neural Networks.", The IEEE International Conference on Hybrid Intelligent Systems (HIS2012)., Pune. India. , 4-7 Dec. 2012,, pp. 96 - 102, 2012. Abstract

The objective of this paper is to evaluate a new combined approach intended for reliable CT liver image segmentation, to separate the liver from other organs, and segment the liver into a set of regions of interest (ROIs). The approach combines the level set with watershed approach used as post segmentation step to produce a reliable segmentation result. Features of first order statistics and grey-level cooccurrence matrix, are calculated and passed to an artificial neural network, to be trained and to classify infected regions. Filtering is used before the segmentation approach to enhance contrast, remove noise and emphasize certain features, as well as connecting ribs around the liver. To evaluate the performance of presented approach, we performed many tests on different CT liver images. The experimental results obtained, show that the overall accuracy offered by the proposed approach is 92.1% in segmenting CT liver images into set of regions even with noise, and 88.9% average accuracy for neural network classification.

Abdalla Zidan, N. I.Ghali, A. E. Hassanien, H. Hefny, and J. Hemanth, "Level Set-based CT Liver Computer Aided Diagnosis System. . ", International Journal of Imaging and Robotic Systems, , vol. 7, issue S13, 2013.
Abdalla Zidan, N. I. Ghali, A. Hassanien, H. Hefny, and J. Hemanth, "Level set-based CT liver computer aided diagnosis system", Int. J. Imaging Robot, vol. 9, pp. 26–36, 2013. Abstract
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Abdalla Zidan, N. I. Ghali, A. ella Hassamen, and H. Hefny, "Level set-based CT liver image segmentation with watershed and artificial neural networks", Hybrid Intelligent Systems (HIS), 2012 12th International Conference on: IEEE, pp. 96–102, 2012. Abstract
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Abd-Elmonim, W. G., N. I. Ghali, A. E. Hassanien, and A. Abraham, "Known-plaintext attack of DES-16 using Particle Swarm Optimization", Nature and Biologically Inspired Computing (NaBIC), 2011 Third World Congress on: IEEE, pp. 12–16, 2011. Abstract
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Abd-Elmonim, W. G., N. I. Ghali, A. E. Hassanien, and A. Abraham, "Known-plaintext attack of DES-16 using Particle Swarm Optimization", Nature and Biologically Inspired Computing (NaBIC), 2011 Third World Congress on: IEEE, pp. 12–16, 2011. Abstract
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ella and A. I. Hafez, E. T. Al-Shammari, A. H. F. A. A., "Community Detection in Social Networks Using Logic-Based Probabilistic Programming, ", Int. J. of Social Network Mining (IJSNM), , vol. 2, issue 3, 2014.
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"Hassanien, A. E. ", Advances in Robotics and Virtual Reality, , Intelligent Systems Reference Library, Vol. 26, Springer - London, 2011. AbstractWebsite

Beyond human knowledge and reach, robotics is strongly involved in tackling challenges of new emerging multidisciplinary fields. Together with humans, robots are busy exploring and working on the new generation of ideas and problems whose solution is otherwise impossible to find. The future is near when robots will sense, smell and touch people and their lives. Behind this practical aspect of human-robotics, there is a half a century spanned robotics research, which transformed robotics into a modern science. The Advances in Robotics and Virtual Reality is a compilation of emerging application areas of robotics. The book covers robotics role in medicine, space exploration and also explains the role of virtual reality as a non-destructive test bed which constitutes a premise of further advances towards new challenges in robotics. This book, edited by two famous scientists with the support of an outstanding team of fifteen authors, is a well suited reference for robotics researchers and scholars from related disciplines such as computer graphics, virtual simulation, surgery, biomechanics and neuroscience.