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    Saliency detection in MPEG and HEVC video using intra-frame and inter-frame distances 

    Shanableh, Tamer (Springer, 2016-04)
    This paper proposes a video saliency detection model for MPEG and HEVC coded videos. The model extracts features from MPEG macro blocks and HEVC coding units. The feature variables are based on syntax elements and statistics ...
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    Spatio-Temporal Feature-Extraction Techniques for Isolated Gesture Recognition in Arabic Sign Language 

    Shanableh, Tamer; Assaleh, Khaled; Al-Rousan, Mohammad (IEEE, 2007)
    This paper presents various spatio-temporal feature-extraction techniques with applications to online and offline recognitions of isolated Arabic Sign Language gestures. The temporal features of a video-based gesture are ...
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    Glove-Based Continuous Arabic Sign Language Recognition in User-Dependent Mode 

    Tubaiz, Noor Ali; Shanableh, Tamer; Assaleh, Khaled (IEEE, 2015)
    In this paper we propose a glove-based Arabic sign language recognition system using a novel technique for sequential data classification. We compile a sensor-based dataset of 40 sentences using an 80-word lexicon. In the ...
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    FPGA-Based Network Traffic Classification Using Machine Learning 

    Elnawawy, Mohammed; Sagahyroon, Assim; Shanableh, Tamer (IEEE Xplore, 2020)
    Real-time classification of internet traffic is critical for the efficient management of networks. Classification approaches based on machine learning techniques have shown promising results with high levels of accuracy. ...
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    Telescopic Vector Composition and Polar Accumulated Motion Residuals for Feature Extraction in Arabic Sign Language Recognition 

    Shanableh, Tamer; Assaleh, Khaled (Springer, 2007)
    This work introduces two novel approaches for feature extraction applied to video-based Arabic sign language recognition, namely, motion representation through motion estimation and motion representation through motion ...
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    Novel Feature Extraction and Classification Technique for Sensor-Based Continuous Arabic Sign Language Recognition 

    Tuffaha, Mohammed; Shanableh, Tamer; Assaleh, Khaled (Springer, 2015)
    This paper proposes a novel approach to continuous Arabic Sign Language recognition. We use a dataset which contains 40 sentences composed from 80 sign language words. The dataset is collected using sensor-based gloves. ...
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    Multiple Proposals for Continuous Arabic Sign Language Recognition 

    Hassan, Mohamed; Assaleh, Khaled; Shanableh, Tamer (Springer, 2019)
    The deaf community relies on sign language as the primary means of communication. For the millions of people around the world who suffer from hearing loss, interaction with hearing people is quite difficult. The main ...
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    User-independent recognition of Arabic sign language for facilitating communication with the deaf community 

    Shanableh, Tamer; Assaleh, Khaled (Elsevier, 2011)
    This paper presents a solution for user-independent recognition of isolated Arabic Sign language gestures. The video based gestures are preprocessed to segment out the hands of the signer based on color segmentation of the ...

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    Author
    Shanableh, Tamer (8)
    Assaleh, Khaled (6)Al-Rousan, Mohammad (1)Elnawawy, Mohammed (1)Hassan, Mohamed (1)Sagahyroon, Assim (1)Tubaiz, Noor Ali (1)Tuffaha, Mohammed (1)Subject
    Feature extraction (8)
    Pattern classification (4)Sign language recognition (3)Motion analysis (2)Arabic sign language recognition (1)Classification Accuracy (1)Digital video/image processing (1)Feature Vector (1)FPGA (1)Frequency Domain (1)... View MoreDate Issued2010 - 2020 (6)2007 - 2009 (2)Has File(s)
    Yes (8)

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