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This booklet constitutes the refereed lawsuits of the second one overseas convention on complicated computing device studying applied sciences and functions, AMLTA 2014, held in Cairo, Egypt, in November 2014. The forty nine complete papers provided have been rigorously reviewed and chosen from a hundred and one preliminary submissions. The papers are geared up in topical sections on computing device studying in Arabic textual content acceptance and assistive know-how; advice platforms for cloud prone; laptop studying in watermarking/authentication and digital machines; beneficial properties extraction and type; rough/fuzzy units and functions; fuzzy multi-criteria determination making; Web-based software and case-based reasoning development; social networks and massive facts sets.
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Additional resources for Advanced Machine Learning Technologies and Applications: Second International Conference, AMLTA 2014, Cairo, Egypt, November 28-30, 2014. Proceedings
Aly and S. Mohammed or any additional hardware, it provides a more natural environment to capture the gesture data . Vision-based recognition systems can be classiﬁed into two categories: appearance-based and geometric-based methods . Although there are a lot of works have been done in sign language, less research attention have been achieved in ArSL. There have been only few research studies on alphabet ArSL. A colored glove for data collection and Adaptive NeuroFuzzy Inference Systems (ANFIS)  was used to recognize isolated signs for 28 alphabets.
S. ) ICONIP 2012, Part II. LNCS, vol. 7664, pp. 85–91. Springer, Heidelberg (2012) 14. : A KNN-SVM hybrid model for cursive handwriting recognition. In: Proceedings of the International Conference on Neural Networks (IJCNN), Brazil, pp. 1–8 (2012) 15. : Rough computing: Theories, technologies and applications. lb Abstract. Smart phone technology and mobile applications have become an indispensable part of our daily life. The primary use however, is targeted towards social media and photography.
In: Advances in Information Sciences and Service Sciences, vol. 2 (2010) 11. : Arabic handwriting recognition using Gabor wavelet transform and SVM. In: Signal Processing (ICSP), Germany (2012) Arabic Character Recognition Based M-SVM: Review 25 12. de/ 13. : Off-line handwritten arabic word recognition using SVMs with normalized poly kernel. S. ) ICONIP 2012, Part II. LNCS, vol. 7664, pp. 85–91. Springer, Heidelberg (2012) 14. : A KNN-SVM hybrid model for cursive handwriting recognition. In: Proceedings of the International Conference on Neural Networks (IJCNN), Brazil, pp.