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• W4386432099 abstract "With the current day complexification of image manipulation technologies (ranging from colour editing or aspect ratio modifications to AI generated fake news), myriad of numerical representations can be connected to a same semantic visual content. Thus, ensuring trust and authenticity for tracking near-duplicated visual content ( <italic xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>i.e</i> ., semantically identical yet digitally different contents) becomes challenging from both methodological and technical points of view. Addressing these challenges requires the synergistic combination of methodological solutions stemming from different research fields, while current solutions are heterogeneous and lack interoperability. In this paper, we bring forth an automatic full lifecycle management workflow for visual content assets represented on blockchains. The workflow is supported by a novel architecture seamlessly integrating near-duplicated content detection, Smart Contract automation, and token brokerage. The architecture leverages a load balancing framework and near-duplicated content detection to grant properties natively featured by blockchains (security, trust, and transparency) to the authentication of assets in environments where the same semantic content has various digital representations. Subsequently minted blockchain assets can then be used contingently with other state-of-the-art tools, ensuring interoperability with blockchain working standards. The effectiveness of this workflow is demonstrated through open-source example implementations for the Ethereum and Tezos frameworks, illustrating the benefits this process brings to automatic asset generation and Intellectual Property Rights (IPR) management." @default.
• W4386432099 created "2023-09-05" @default.
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• W4386432099 date "2023-01-01" @default.
• W4386432099 modified "2023-09-27" @default.
• W4386432099 title "Blockchain asset lifecycle management for visual content tracking" @default.
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• W4386432099 doi "https://doi.org/10.1109/access.2023.3311635" @default.
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