Publications

Export 33 results:
Sort by: Author [ Title  (Asc)] Type Year
A B C D E F G H I J K L M N O P Q R S T U [V] W X Y Z   [Show ALL]
A
Václav Snášel, A. Keprt, A. Abraham, and A. E. Hassanien, "Approximate string matching by fuzzy automata", Man-Machine Interactions: Springer Berlin Heidelberg, pp. 281–290, 2009. Abstract
n/a
Václav Snášel, A. Keprt, A. Abraham, and A. E. Hassanien, "Approximate string matching by fuzzy automata", Man-Machine Interactions: Springer Berlin Heidelberg, pp. 281–290, 2009. Abstract
n/a
Soliman, O. S., Jan Platoš, A. E. Hassanien, and Václav Snášel, "Automatic localization and boundary detection of retina in images using basic image processing filters", Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011: Springer Berlin Heidelberg, pp. 169–182, 2013. Abstract
n/a
Soliman, O. S., Jan Platoš, A. E. Hassanien, and Václav Snášel, "Automatic localization and boundary detection of retina in images using basic image processing filters", Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011: Springer Berlin Heidelberg, pp. 169–182, 2013. Abstract
n/a
Soliman, O. S., Jan Platoš, A. E. Hassanien, and Václav Snášel, "Automatic localization and boundary detection of retina in images using basic image processing filters", Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011: Springer Berlin Heidelberg, pp. 169–182, 2013. Abstract
n/a
B
Hassanien, A. E., N. El-Bendary, M. Kudělka, and Václav Snášel, "Breast cancer detection and classification using support vector machines and pulse coupled neural network", Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011: Springer Berlin Heidelberg, pp. 269–279, 2013. Abstract
n/a
Hassanien, A. E., N. El-Bendary, M. Kudělka, and Václav Snášel, "Breast cancer detection and classification using support vector machines and pulse coupled neural network", Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011: Springer Berlin Heidelberg, pp. 269–279, 2013. Abstract
n/a
Hassanien, A. E., N. El-Bendary, M. Kudělka, and Václav Snášel, "Breast cancer detection and classification using support vector machines and pulse coupled neural network", Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011: Springer Berlin Heidelberg, pp. 269–279, 2013. Abstract
n/a
D
TarasKotyk, N. D., A. S. Ashour, A. D. C. Victoria, T. Gaber, A. E. Hassanien, and V. Snasel, "Detection of Dead stained microscopic cells based on Color Intensity and Contrast", The 1st International Conference on Advanced Intelligent System and Informatics (AISI2015), 2015, , Beni Suef, Egypt, November 28-30, , 2015. Abstract

Apoptosis is an imperative constituent of various processes including proper progression and functioning of the immune system, embryonic development as well as chemical-induced cell death. Improper apoptosis is a reason in numerous human/animal’s conditions involving ischemic damage, neurodegenerative diseases, autoimmune disorders and various types of cancer. An outstanding feature of neurodegenerative diseases is the loss of specific neuronal populations. Thus, the detection of the dead cells is a necessity. This paper proposes a novel algorithm to achieve the dead cells detection based on color intensity and contrast changes and aims for fully automatic apoptosis detection based on image analysis method. A stained cultures images using Caspase stain of albino rats hippocampus specimens using light microscope (total 21 images) were used to evaluate the system performance. The results proved that the proposed system is efficient as it achieved high accuracy (98.89 ± 0.76 %) and specificity (99.36 ± 0.63 %) and good mean sensitivity level of (72.34 ± 19.85 %).

F
Hassanien, A. - E., A. Abraham, A. V. Vasilakos, and W. Pedrycz, Foundations of Computational Intelligence: Volume 1: Learning and Approximation, : Springer, 2009. Abstract
n/a
Horàk, Z., Václav Snášel, A. Abraham, and A. E. Hassanien, "Fuzzified Aho-Corasick Search Automata", Information Assurance and Security (IAS), 2010 Sixth International Conference on: IEEE, pp. 338–342, 2010. Abstract
n/a
Horàk, Z., Václav Snášel, A. Abraham, and A. E. Hassanien, "Fuzzified Aho-Corasick Search Automata", Information Assurance and Security (IAS), 2010 Sixth International Conference on: IEEE, pp. 338–342, 2010. Abstract
n/a
Abder-Rahman Ali, Micael Couceiro, A. E. Hassanien, M. F. Tolba, and Václav Snášel, "Fuzzy c-means based liver ct image segmentation with optimum number of clusters", Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014: Springer International Publishing, pp. 131–139, 2014. Abstract
n/a
Ho, S. H., A. E. Hassanien, N. Van Du, Q. Salih, and H. Sooi, "FUZZY C-MEANS CLUSTERING WITH ADJUSTABLE FEATURE WEIGHTING DISTRIBUTION FOR BRAIN MRI VENTRICLES SEGMENTATION Kai Xiao1", Update, vol. 15, pp. 1, 2001. Abstract
n/a
L
Abder-Rahman Ali, Micael Couceiro, A. M. Anter, A. E. Hassanien, M. F. Tolba, and Václav Snášel, "Liver CT Image Segmentation with an Optimum Threshold Using Measure of Fuzziness", Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014: Springer International Publishing, pp. 83–92, 2014. Abstract
n/a
M
Hassanien, A. E., H. Al-Qaheri, Václav Snášel, and J. F. Peters, "Machine learning techniques for prostate ultrasound image diagnosis", Advances in Machine Learning I: Springer Berlin Heidelberg, pp. 385–403, 2010. Abstract
n/a
Hassanien, A. E., H. Al-Qaheri, Václav Snášel, and J. F. Peters, "Machine learning techniques for prostate ultrasound image diagnosis", Advances in Machine Learning I: Springer Berlin Heidelberg, pp. 385–403, 2010. Abstract
n/a
N
Ali, A. F., A. E. Hassanien, and Václav Snášel, "The nelder-mead simplex method with variables partitioning for solving large scale optimization problems", Innovations in Bio-inspired Computing and Applications: Springer International Publishing, pp. 271–284, 2014. Abstract
n/a
Ali, A. F., A. E. Hassanien, and Václav Snášel, "The Nelder-Mead Simplex Method with Variables Partitioning for Solving Large Scale Optimization Problems.", Innovations in Bio-inspired Computing and Applications. Advances in Intelligent Systems and Computing(Springer) , Czech republic , Volume 237, pp. 271-284, 2013.
Ali, A. F., A. E. Hassanien, Václav Snášel, and M. F. Tolba, "A New Hybrid Particle Swarm Optimization with Variable Neighborhood Search for Solving Unconstrained Global Optimization Problems", Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014: Springer International Publishing, pp. 151–160, 2014. Abstract
n/a
Kudelka, M., V. Snasel, Z. Horak, A. E. Hassanien, A. Abraham, and J. D. Velásquez, "A novel approach for comparing web sites by using MicroGenres", Engineering Applications of Artificial Intelligence,, vol. 35, pp. 178-198, 2014. AbstractWebsite

In this paper, a novel approach is introduced to compare web sites by analysing their web page content. Each web page can be expressed as a set of entities called MicroGenres, which in turn are abstractions about design patterns and genres for representing the page content. This description is useful for web page and web site classification and for a deeper insight into the web site׳s social context.

The web site comparison is useful for extracting patterns which can be used for improving Web search engine effectiveness, the identification of best practices in web site design and of course in the organization of web page content to personalize the web user experience on a web site.

The effectiveness of the proposed approach was tested in a real world case, with e-shop web sites showing that a web site can be represented in a high level of abstraction by using MicroGenres, the contents of which can then be compared and given a measure corresponding to web site similarity. This measure is very useful for detecting web communities on the Web, i.e., a group of web sites sharing similar contents, and the result is essential in performing a focused and effective information search as well as minimizing web page retrieval.

Kudelka, M., V. Snasel, Z. Horak, A. E. Hassanien, A. Abraham, and J. D. Velásquez, "A novel approach for comparing web sites by using MicroGenres", Engineering Applications of Artificial Intelligence, vol. 35: Pergamon, pp. 187–198, 2014. Abstract
n/a
O
Moustafa Zein, Ahmed Abdo, A. Adl, A. E. Hassanien, M. F. Tolba, and Václav Snášel, "Orphan Drug Legislation with Data Fusion Rules Using Multiple Fingerprints Measurements", Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014: Springer International Publishing, pp. 261–270, 2014. Abstract
n/a
P
Abraham, A., K. Wegrzyn-Wolska, A. E. Hassanien, Václav Snášel, and A. M. Alimi, Proceedings of the Second International Afro-European Conference for Industrial Advancement AECIA 2015, : Springer, 2016. Abstract
n/a
R
Esraa Elhariri, N. El-Bendary, A. E. Hassanien, A. Badr, A. M. M. Hussein, and Václav Snášel, "Random forests based classification for crops ripeness stages", Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014: Springer International Publishing, pp. 205–215, 2014. Abstract
n/a