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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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Wanas, N., M. El-Saban, H. Ashour, and W. Ammar, "Automatic scoring of online discussion posts", Proceedings of the 2Nd ACM Workshop on Information Credibility on the Web, pp. 19–26, 2008. Abstract
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Gomaa, W. H., and A. A. Fahmy, "Automatic scoring for answers to Arabic test questions", Computer Speech & Language, vol. 28, issue 4, pp. 833-857, 2014. fca58871a4bdb57ef6cf40030733ce01.pdf
Shaalan, K., and A. H. Hossny, "Automatic rule induction in Arabic to English machine translation framework", Challenges for Arabic Machine Translation, Amsterdam, The Netherlands, John Benjamins Publishing Company, 2012. Abstractkhaled_shaalan_ch10.pdf

This paper addresses exploiting a supervised machine learning technique to automatically induce Arabic-to-English transfer rules from chunks of parallel aligned linguistic resources. The induced structural transfer rules encode the linguistic translation knowledge for converting an Arabic syntactic structure into a target English syntactic structure. These rules are going to be an integral part of an Arabic-English transfer-based machine translation. Nevertheless, a novel morphological rule induction method is employed for learning Arabic morphological rules that are applied in our Arabic morphological analyzer. To demonstrate the capability of the automated rule induction technique we conducted rule-based translation experiments that use induced rules from a relatively small data set. The translation quality of the hybrid translation experiments achieved good results in terms of WER.

Mustafa, H. H., and N. R. Darwish, "Automatic Requirement Classification Technique: Using Different Stemming Algorithms", International Journal of Data Mining and Knowledge Engineering, ISSN: 0974-9578, vol. 10, issue 6: Coimbatore Institute of Information Technology, pp. 122-127, 2018. Abstract
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Khalel, A., and M. El-Saban, "Automatic pixelwise object labeling for aerial imagery using stacked u-nets, arXiv 2018", arXiv preprint arXiv:1803.04953, Submitted. Abstract
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Khalel, A., and M. El-Saban, "Automatic pixelwise object labeling for aerial imagery using stacked u-nets", arXiv preprint arXiv:1803.04953, 2018. Abstract
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El-Bialy, A., and A. H. Kandil, "Automatic orthodontic clinical system", International Conference on Electronic and Computer Engineering, pp. 358-363, 2004.
El-Bialy, A., and A. H. Kandil, "Automatic orthodontic clinical system", Electrical, Electronic and Computer Engineering, 2004. ICEEC'04. 2004 International Conference on: IEEE, pp. 358–363, 2004. Abstract
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Saleh, I., and N. El-Tazi, "Automatic Organization of Semantically Related Tags Using Topic Modelling", 1st International Workshop on Data Science: Methodologies and Use-Cases (DaS 2017), In conjunction with the 21th European Conference on Advances in Databases and Information Systems (ADBIS 2017), Nicosia, Cyprus, pp. 235-245, 2017. das_paper_cr.pdf
Saleh, I., and N. E. -, "Automatic Organization of Semantically Related Tags Using Topic Modelling", New Trends in Databases and Information Systems - {ADBIS} 2017 Short Papers and Workshops, AMSD, BigNovelTI, DAS, SW4CH, DC, Nicosia, Cyprus, September 24-27, 2017, Proceedings, pp. 235–245, 2017. Abstract
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Saleh, I., and N. E. -, "Automatic Organization of Semantically Related Tags Using Topic Modelling", New Trends in Databases and Information Systems - {ADBIS} 2017 Short Papers and Workshops, AMSD, BigNovelTI, DAS, SW4CH, DC, Nicosia, Cyprus, September 24-27, 2017, Proceedings, pp. 235–245, 2017. Abstract
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Taha, E. M., E. Emary, and K. Moustafa, "Automatic Optical Inspection for PCB Manufacturing: a Survey", International Journal of Scientific & Engineering Research, vol. 5, issue 7, pp. 1095-1102, 2014.
Badr, A., M. M. Abdelwahab, and A. M. Thabet, Automatic Number Plate Recognition System, , vol. 38, 2011. Abstract
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Badr, A., M. M. Abdelwahab, A. M. Thabet, and A. M. Abdelsadek, "Automatic Number Plate Recognition System", Annals of the University of Craiova-Mathematics and Computer Science Series, vol. 38, no. 1, pp. 62–71, 2011. Abstract
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A.Badr, M.AbdWahab, A.Thabet, and A.Sadek, "Automatic Number Plate Recognition System", Annals of the University of Craiova, vol. 38, pp. 62-71, 2011. Abstract

Automatic recognition of car license plate number became a very important in our daily life because of the unlimited increase of cars and transportation systems which make it impossible to be fully managed and monitored by humans, examples are so many like traffic monitoring, tracking stolen cars, managing parking toll, red-light violation enforcement, border and customs checkpoints. Yet it’s a very challenging problem, due to the diversity of plate formats, different scales, rotations and non-uniform illumination conditions during image acquisition. This paper mainly introduces an Automatic Number Plate Recognition System (ANPR) using Morphological operations, Histogram manipulation and Edge detection Techniques for plate localization and characters segmentation. Artificial Neural Networks are used for character classification and recognition.

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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A, H., S. K, and F. A, "Automatic Morphological Rule Induction for Arabic ", In the Proceedings of The LREC'08 workshop on HLT & NLP within the Arabic world: Arabic Language and local languages processing: Status Updates and Prospects, Morocco, May , 2008.
Hossny, A., K. Shaalan, and A. Fahmy, "Automatic Morphological Rule Induction for Arabic", The sixth international conference on Language Resources and Evaluation (LREC'08) workshop on HLT & NLP within the Arabic world: Arabic Language and local languages processing: Status Updates and Prospects, Marrakech, Morocco, LREC, pp. 97–101, may, 2008. Abstractautomaticruleinduction.pdf

In this paper, we introduce an algorithm for morphological rule induction using meta-rules for Arabic morphology based on inductive logic programming. The processing resources are a set of example pairs (stem and inflected form) with their feature vectors, either positive or negative, and the linguistic background knowledge from the Arabic morphological analysis domain. Each example pair has two words to be analyzed vocally into consonants and vowels. The algorithm applies two levels of mapping: between the vocal representation of the two words (stem, morphed) and between their feature vector. It differentiates between both mappings in order to accurately deduce which changes in the word structure led to which changes in its features. The paper also addresses the irregularity, productivity and model consistency issues. We have developed an Arabic morphological rule induction system (AMRIS). Successful evaluation has been performed and showed that the system performance results achieved were satisfactory.

Shaalan, K., H. Talhami, and I. Kamel, "Automatic Morphological Generation for the Indexing of Arabic Speech Recordings", The International Journal of Computer Processing of Oriental Languages (IJCPOL), vol. 20, no. 1, pp. 1–14, 2007. Abstractijcpol2.pdfWebsite

This paper presents a novel Arabic morphological generator (AMG) for Modern Standard Arabic (MSA) which is designed and implemented using Prolog. The AMG is used to generate inflected forms of words used for the indexing of Arabic audio. These words are also the relevant terms in the Arab authority system (library information retrieval system) used in this study. The AMG generates inflected Arabic words from the root according to pre-specified morphological features that can be extended as needed. The Arabic word is represented as a feature structure which is handled through unification during the morphological generation process. The inflected forms can then be inserted automatically into a speech recognition grammar which is used to identify these words in an audio sequence or utterance.

Mostafa, E., A. E. F. A. Hegazy, and A. Badr, "Automatic Mass Detection and Classification in Mammograms", Egyptian Computer Science Journal, vol. 30, pp. 14–24, 2008. Abstract
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E.Mostafa, A.Hegazy, and A.Badr, "Automatic mass detection and classification in mammograms", Egyptian Computer Science Journal, 2009.
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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Tourism