Continuous Sign Language Recognition: Dataset Development and Novel Frameworks

Continuous Sign Language Recognition: Dataset Development and Novel Frameworks

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	unknown (author)
التنسيق:	masterThesis
منشور في:	2020
الموضوعات:	Computer
الوصول للمادة أونلاين:	https://eprints.kfupm.edu.sa/id/eprint/143344/4/Sarah_Alyami_PhD_Thesis_June23.pdf
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

مواد مشابهة

Multiple Proposals for Continuous Arabic Sign Language Recognition
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منشور في: (2019)

Sensor-based Continuous Arabic Sign Language Recognition
حسب: Tubaiz, Noor Ali
منشور في: (2014)

Arabic Sign Language Recognition
حسب: unknown
منشور في: (2020)

Continuous Arabic Sign Language Recognition in User Dependent Mode
حسب: Assaleh, Khaled
منشور في: (2010)

Novel Feature Extraction and Classification Technique for Sensor-Based Continuous Arabic Sign Language Recognition
حسب: Tuffaha, Mohammed
منشور في: (2015)

Sensor-Based Signer Independent Continuous Arabic Sign Language Recognition
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منشور في: (2017)

Automation of the Arabic sign language recognition
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منشور في: (2004)

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منشور في: (2015)

HAND GESTURE SEGMENTATION AND SIGN LANGUAGE RECOGNITION USING DEEP LEARNING
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منشور في: (2020)

Motion Images with Positioning Information and Deep Learning for Continuous Arabic Sign Language Recognition in Signer Dependent and Independent Modes
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منشور في: (2024)

A New Approach to Arabic Sign Language Recognition System
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منشور في: (2020)

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منشور في: (2004)

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حسب: ALMAHRI, HAMDA GHALIB AWADH ALI
منشور في: (2022)

Two-Stage Deep Learning Solution for Continuous Arabic Sign Language Recognition Using Word Count Prediction and Motion Images
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منشور في: (2023)

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ARABIC SIGN LANGUAGE MACHINE TRANSLATION
حسب: unknown
منشور في: (2020)

User-independent recognition of Arabic sign language for facilitating communication with the deaf community
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منشور في: (2011)

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منشور في: (2007)

Telescopic Vector Composition and Polar Accumulated Motion Residuals for Feature Extraction in Arabic Sign Language Recognition
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حسب: unknown
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