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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
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Ahmed M. Anter, M. A. Elsoud, and A. E. Hassanien, "Automatic Mammographic Parenchyma Classification According to BIRADS Dictionary", Computer Vision and Image Processing in Intelligent Systems and Multimedia Technologies, USA, IGI, pp. 22-37,, 2014. Abstract

Internal.density.of.the.breast.is.a.parameter.that.clearly.affects.the.performance.of.segmentation.and.
classification.algorithms.to.define.abnormality.regions..Recent.studies.have.shown.that.their.sensitivity.
is.significantly.decreased.as.the.density.of.the.breast.is.increased..In.this.chapter,.enhancement.and. segmentation.processis applied to increase the computation and focus onmammographic parenchyma.
This.parenchyma is analyzed to discriminate tissue density according to BIRADS using Local Binary
Pattern.(LBP),.Gray.Level.Co-Occurrence.Matrix.(GLCM),.Fractal.Dimension.(FD),.and.feature.fusion.
technique.is.applied.to.maximize.and.enhance.the.performance.of.the.classifier.rate..The.different.methods.
for.computing.tissue.density.parameter.are.reviewed,.and.the.authors.also.present.and.exhaustively.
evaluate.algorithms.using.computer.vision.techniques..The.experimental.results.based.on.confusion.
matrix.and.kappa.coefficient.show.a.higher.accuracy.is.obtained.by.automatic.agreement.classification.

Anter, A. M., M. A. Elsoud, and A. E. Hassanien, "Automatic mammographic parenchyma classification according to BIRADS dictionary", Computer Vision and Image Processing in Intelligent Systems and Multimedia Technologies. IGI Global, pp. 22–37, 2014. Abstract
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Fouad, M. M. M., H. zawbaa, N. Elbendary, and H. Aboul Ella, "Automatic Nile Tilapia Fish Classification Approach using Machine Learning Techniques", 13th IEEE International Conference on Hybrid Intelligent Systems |(HIS13) Tunisia, 4-6 Dec. pp. 173-179, , Tunisia, , 4-6 Dec, 2013.
Fouad, M. M. M., H. M. Zawbaa, N. El-Bendary, and A. E. Hassanien, "Automatic nile tilapia fish classification approach using machine learning techniques", Hybrid Intelligent Systems (HIS), 2013 13th International Conference on: IEEE, pp. 173–178, 2013. Abstract
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Anter, A. M., A. E. Hassanien, and G. Schaefer, "Automatic Segmentation and Classification of Liver Abnormalities Using Fractal Dimension", 2nd IAPR Asian Conference on Pattern Recognition (ACPR), 2013 , Okinawa, Japan. , 5 Nov. , 2013.
Anter, A. M., A. E. Hassanien, and G. Schaefer, "Automatic Segmentation and Classification of Liver Abnormalities Using Fractal Dimension", Pattern Recognition (ACPR), 2013 2nd IAPR Asian Conference on: IEEE, pp. 937–941, 2013. Abstract
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Zawbaa, H. M., and A. E. Hassanien, Automatic Soccer Video Summarization, , Cairo, Cairo Unversity, 2012. Abstract

This thesis presents an automatic soccer video summarization system using machine learning (ML) techniques. The proposed system is composed of ve phases. Namely; in the pre-processing phase, the system segments the whole video stream into small video shots. Then, in the shot processing
phase, it applies two types of classi cation (shot type classi cation and play / break classification) to the video shots resulted from the pre-processing phase. Afterwards, in the replay detection phase, the proposed system applies two machine learning algorithms, namely; support vector machine (SVM) and arti cial neural network (ANN), for emphasizing important segments with championship logo appearance. Also, in the excitement event detection phase, the proposed system uses both machine learning algorithms for detecting the scoreboard which contain an information about the score of the game. The proposed system also uses k-means algorithm and Hough line transform for detecting vertical goal posts and Gabor lter for detecting goal net. Finally, in the event detection and summarization phase, the proposed system highlights the most important events during the match. Experiments on real soccer videos demonstrate encouraging results. The event detection and summarization has attained recall 94% and precision 97.3% for soccer match videos from ve international soccer championships.

Zawbaa, H. M., and A. E. Hassanien, Automatic Soccer Video Summarization, : Cairo Unversity, 2012. Abstract
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Xiao, K., S. H. Ho, and others, "Automatic unsupervised segmentation methods for mri based on modified fuzzy c-means", Fundamenta Informaticae, vol. 87, no. 3-4: IOS Press, pp. 465–481, 2008. Abstract
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Xiao, K., S. H. Ho, and others, "Automatic unsupervised segmentation methods for mri based on modified fuzzy c-means", Fundamenta Informaticae, vol. 87, no. 3-4: IOS Press, pp. 465–481, 2008. Abstract
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Alaa Tharwat, B. E. Elnaghi, A. M. Ghanem, and A. E. Hassanien, "Automatically Human Age Estimation Approach via Two-Dimensional Facial Image Analysis", International Conference on Advanced Intelligent Systems and Informatics: Springer International Publishing, pp. 491–501, 2016. Abstract
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