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This booklet constitutes the refereed lawsuits of the second one foreign convention on complicated laptop studying applied sciences and purposes, AMLTA 2014, held in Cairo, Egypt, in November 2014. The forty nine complete papers awarded have been conscientiously reviewed and chosen from one zero one preliminary submissions. The papers are equipped in topical sections on computer studying in Arabic textual content acceptance and assistive expertise; advice structures for cloud prone; laptop studying in watermarking/authentication and digital machines; beneficial properties extraction and class; rough/fuzzy units and purposes; fuzzy multi-criteria selection making; Web-based software and case-based reasoning development; social networks and large information sets.
Read Online or Download Advanced Machine Learning Technologies and Applications: Second International Conference, AMLTA 2014, Cairo, Egypt, November 28-30, 2014. Proceedings PDF
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Extra info for Advanced Machine Learning Technologies and Applications: Second International Conference, AMLTA 2014, Cairo, Egypt, November 28-30, 2014. Proceedings
1 illustrates the proposed system architecture; it manifests the system constituting components and the way they are connected to each other. Firstly, the signer performs word gestures in front of a camera then the gesture video is segmented into frames, the captured image sequence is then preprocessed before feature extraction. The region of interest for all signs are head and hands parts only, these regions are segmented using an eﬃcient skin color model. The skin map is further analyzed to crop the hand and head regions, the cropped image is then rescaled to ﬁxed size.
Only few of these mobile apps have surpassed the purpose of being an added value to our daily life, to becoming a crucial tool. Applications crafted for people with disabilities have emerged lately to help them achieve more what they could do before the Smartphone era. Visually impaired and blind people find it difficult to face their day-to-day problems because of their impairment. 6% of the world’s total population was visually imapried. In spite of the advancement in technology, there is no complete cure for such problems and they need some assistance to complete their daily tasks.
Two main approaches were considered: SURF [ and ORB . SURF, or Speeded Up Robust R Features, is a scale and rotation invariant detecctor and descriptor. SURF em mploys Hessian-Laplace matrix detectors to find inteerest points. A feature vector (or descriptor) is then computed to describe the neighborhoood of the interest point, by means m of local-sensitivity hashing (LSH) [17,18]. SU URF relies on Euclidean distancee between the matched descriptor and the most similar oone. Distances below a certain n pre-determined threshold are chosen as good matchhes.