0000000000344100

AUTHOR

Abdelhak Belhi

showing 7 related works from this author

Digital Heritage Enrichment through Artificial Intelligence and SemanticWeb Technologies

2019

Art and culture represent substantial ways to transfer the history of humans across civilizations and epochs. Preserving artwork and cultural objects is thus important and the focus of multiple institutions and governments around the world. Digital preservation in cultural heritage represents a cost-effective and reliable long-term preservation and several challenges related to its effectiveness and its reliability have arisen such as metadata enrichment, digital curation, link discoveries, etc. Through this paper, we discuss these challenges and present innovative ways that leverage recent endeavors in artificial intelligence and semantic web technologies to enrich cultural data. Our contr…

World Wide WebArtificial intelligenceEngineeringDigital heritagebusiness.industryCultural heritageDeep learningDigital heritageCEPROQHA projectbusinessSemantic web2019 4th International Conference on Communication and Information Systems (ICCIS)
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Towards a Hierarchical Multitask Classification Framework for Cultural Heritage

2018

Digital technologies such as 3D imaging, data analytics and computer vision opened the door to a large set of applications in cultural heritage. Digital acquisition of a cultural assets takes nowadays a couple of seconds thanks to the achievements in 2D and 3D acquisition technologies. However, enriching these cultural assets with labels and relevant metadata is still not fully automatized especially due to their nature and specificities. With the recent publication of several cultural heritage datasets, many researchers are tackling the challenge of effectively classifying and annotating digital heritage. The challenges that are often addressed are related to visual recognition and image c…

Computer scienceData field02 engineering and technology[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Multitask ClassificationCultural diversity0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]Digital preservationComputingMilieux_MISCELLANEOUSContextual image classificationDigital heritagebusiness.industryDeep learningConvolutional Neural Networks[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020206 networking & telecommunicationsData scienceMetadataCultural heritageDigital preservationCultural heritage020201 artificial intelligence & image processingArtificial intelligencebusinessClassifier (UML)
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A Cost-Effective 3D Acquisition and Visualization Framework for Cultural Heritage

2020

Museums and cultural institutions, in general, are in a constant challenge of adding more value to their collections. The attractiveness of assets is practically tightly related to their value obeying the offer and demand law. New digital visualization technologies are found to give more excitements, especially to the younger generation as it is proven by multiple studies. Nowadays, museums around the world are currently trying to promote their collections through new multimedia and digital technologies such as 3D modeling, virtual reality (VR), augmented reality (AR), and serious games. However, the difficulty and the resources required to implement such technologies present a real challen…

Value (ethics)Artificial intelligence3D interaction3D interactionComputer science02 engineering and technologyVirtual realityConstant (computer programming)11. Sustainability0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]CEPROQHA projectComputingMilieux_MISCELLANEOUSMotion controllerbusiness.industryDeep learningDeep learning020207 software engineeringData science3D modellingVisualizationCultural heritageCultural heritage020201 artificial intelligence & image processingAugmented realityArtificial intelligencebusiness
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Digitization and preservation of cultural heritage: The CEPROQHA approach

2017

The humanity has always learned from the previous experiences for many reasons. The national heritage proves to be a great way to discover a nation's history. As a result, these priceless cultural items have a special attention. However, Since the wide adoption of new digital technologies, documenting, storing, and exhibiting cultural heritage assets became more affordable and reliable. These digital records are then used in several applications. Researchers saw the opportunity to use digital heritage recordings for long-term preservation. In this paper, we present the research progress in cultural heritage digital processing and preservation, highlighting the most impactful advances. Addit…

History[ INFO ] Computer Science [cs]Content management system02 engineering and technologySemanticsDigital records01 natural sciences[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]World Wide WebACM: H.: Information SystemsCultural diversity3D Modeling0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs][ INFO.INFO-CL ] Computer Science [cs]/Computation and Language [cs.CL]Digital preservationCEPROQHA projectDigitizationComputingMilieux_MISCELLANEOUSDigital heritage010401 analytical chemistryACM : H.: Information Systems020207 software engineering0104 chemical sciencesCultural heritageSemantic enrichmentDigital preservationHumanityCultural heritageDigital heritage
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Study and Evaluation of Pre-trained CNN Networks for Cultural Heritage Image Classification

2021

The classification of digital images is an essential task during the restoration and preservation of cultural heritage (CH). In computer vision, cultural heritage classification relies on the classification of asset images regarding a certain task such as type, artist, genre, style identification, etc. CH classification is challenging as various CH asset images have similar colors, textures, and shapes. In this chapter, the aim is to study and evaluate the use of pre-trained deep convolutional neural networks such as VGG16, VGG-19, ResNet50, and Inception-V3 for cultural heritage images classification using transfer learning techniques. The main idea is to start with CNN models previously t…

Cultural heritageIdentification (information)Digital imageContextual image classificationComputer sciencebusiness.industryDeep learningPattern recognitionArtificial intelligenceTransfer of learningbusinessConvolutional neural networkTask (project management)
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Digitization and Preservation of Cultural Heritage Products

2017

Cultural heritage encompasses various aspects of a nation's history. Cultural heritage artifacts are considered as priceless items that need special care. Since the wide adoption of new digital technologies, documenting and storing cultural heritage assets became more affordable and reliable. These records are then used in several applications. Researchers saw the opportunity to use digital heritage recordings for long-term preservation. They are considering cultural heritage artifacts as products, and the history behind them as a product lifecycle. In this paper, we present the research progress in cultural heritage digital processing and preservation, highlighting the most impactful advan…

Architectural engineeringEngineering[ INFO ] Computer Science [cs]02 engineering and technologyPlmPLM01 natural sciences3D modelingProduct lifecycle0202 electrical engineering electronic engineering information engineeringDigital preservation[INFO]Computer Science [cs]CEPROQHA projectDigitizationbusiness.industryComputingMethodologies_MISCELLANEOUS010401 analytical chemistry020207 software engineering0104 chemical sciencesSemantic enrichmentCultural heritageDigital preservationCultural heritageDigital heritageSpecial carebusiness
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Deep Learning and Cultural Heritage: The CEPROQHA Project Case Study

2019

Cultural 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 tha…

Progress in artificial intelligenceValue (ethics)Computer sciencebusiness.industryDeep learningmedia_common.quotation_subjectInformation accessContext (language use)Cultural HeritageMissing dataData scienceCultural heritageCEPROQHA ProjectDeep LearningPromotion (rank)Artificial IntelligenceArtificial intelligencebusinessDigital Heritagemedia_common2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)
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