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المؤلفBelhi, Abdelhak
المؤلفGasmi, Houssem
المؤلفAl-Ali, Abdulaziz Khalid
المؤلفBouras, Abdelaziz
المؤلفFoufou, Sebti
المؤلفYu, Xi
المؤلفZhang, Haiqing
تاريخ الإتاحة2023-04-09T08:34:47Z
تاريخ النشر2019
اسم المنشور2019 13th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2019
المصدرScopus
معرّف المصادر الموحدhttp://dx.doi.org/10.1109/SKIMA47702.2019.8982520
معرّف المصادر الموحدhttp://hdl.handle.net/10576/41720
الملخصCultural heritage takes an important part of the history of humankind as it is one of the most powerful tools for the transfer and preservation of moral identity. As a result, these cultural assets are considered highly valuable and sometimes priceless. Digital technologies provided multiple tools that address challenges related to the promotion and information access in the cultural context. However, the large data collections of cultural information have more potential to add value and address current challenges in this context with the recent progress in artificial intelligence (AI) with deep learning and data mining tools. Through the present paper, we investigate several approaches that are used or can potentially be used to promote, curate, preserve and value cultural heritage through new and evolutionary techniques based on deep learning tools. The deep learning approaches entirely developed by our team are intended to classify and annotate cultural data, complete missing data, or map existing data schemes and information to standardized schemes with language processing tools. 2019 IEEE.
راعي المشروعACKNOWLEDGMENT This publication was made possible by NPRP grant 9-181-1-036 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors (www.ceproqha.qa).
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعArtificial Intelligence
CEPROQHA Project
Cultural Heritage
Deep Learning
Digital Heritage
العنوانDeep learning and cultural heritage: The CEPROQHA project case study
النوعConference Paper
dc.accessType Abstract Only


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