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RISS 인기검색어
- 검색키워드
- 저자 : Rahib H.Abiyev (검색결과 2 건)
- 무료
- 기관 내 무료
- 유료
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Sign Language Translation Using Deep Convolutional Neural Networks
( Rahib H. Abiyev ),( Murat Arslan ),( John Bush Idoko ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.2
Sign language is a natural, visually oriented and non-verbal communication channel between people that facilitates communication through facial/bodily expressions, postures and a set of gestures. It is basically used for communication with people who are deaf or hard of hearing. In order to understand such communication quickly and accurately, the design of a successful sign language translation system is considered in this paper. The proposed system includes object detection and classification stages. Firstly, Single Shot Multi Box Detection (SSD) architecture is utilized for hand detection, then a deep learning structure based on the Inception v3 plus Support Vector Machine (SVM) that combines feature extraction and classification stages is proposed to constructively translate the detected hand gestures. A sign language fingerspelling dataset is used for the design of the proposed model. The obtained results and comparative analysis demonstrate the efficiency of using the proposed hybrid structure in sign language translation.
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Personal Iris Recognition Using Neural Network
Rahib H.Abiyev,Koray Altunkaya 보안공학연구지원센터 2008 International Journal of Security and Its Applicat Vol.2 No.2
Iris recognition is one of important biometric recognition approach in a human identification is becoming very active topic in research and practical application. Iris recognition system consists of localization of the iris region and generation of data set of iris images followed by iris pattern recognition. In this paper, a fast algorithm is proposed for the localization of the inner and outer boundaries of the iris region. Located iris is extracted from an eye image, and, after ormalization and enhancement, it is represented by a data set. Using this data set a Neural Network (NN) is used for the classification of iris patterns. The adaptive learning strategy is applied for training of the NN. The results of simulations illustrate the effectiveness of the neural system in personal identification.
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