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Fernando Vilariño. 2019. Public Libraries Exploring how technology transforms the cultural experience of people. Workshop on Social Impact of AI. Open Living Lab Days Conference..
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Fernando Vilariño. 2020. Unveiling the Social Impact of AI. Workshop at Digital Living Lab Days Conference.
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Fernando Vilariño. 2019. 3D Scanning of Capitals at Library Living Lab.
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Fernando Vilariño and Dimosthenis Karatzas. 2015. The Library Living Lab. Open Living Lab Days.
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Fernando Vilariño and Dimosthenis Karatzas. 2016. A Living Lab approach for Citizen Science in Libraries. 1st International ECSA Conference.
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Fernando Vilariño, Dimosthenis Karatzas and Alberto Valcarce. 2018. The Library Living Lab Barcelona: A participative approach to technology as an enabling factor for innovation in cultural spaces.
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Fernando Vilariño, Dimosthenis Karatzas and Alberto Valcarce. 2018. Libraries as New Innovation Hubs: The Library Living Lab. 30th ISPIM Innovation Conference.
Abstract: Libraries are in deep transformation both in EU and around the world, and they are thriving within a great window of opportunity for innovation. In this paper, we show how the Library Living Lab in Barcelona participated of this changing scenario and contributed to create the Bibliolab program, where more than 200 public libraries give voice to their users in a global user-centric innovation initiative, using technology as enabling factor. The Library Living Lab is a real 4-helix implementation where Universities, Research Centers, Public Administration, Companies and the Neighbors are joint together to explore how technology transforms the cultural experience of people. This case is an example of scalability and provides reference tools for policy making, sustainability, user engage methodologies and governance. We provide specific examples of new prototypes and services that help to understand how to redefine the role of the Library as a real hub for social innovation.
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Fernando Vilariño, Dimosthenis Karatzas, Marcos Catalan and Alberto Valcarcel. 2015. An horizon for the Public Library as a place for innovation and creativity. The Library Living Lab in Volpelleres. The White Book on Public Library Network from Diputació de Barcelona.
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Francesc Net, Marc Folia, Pep Casals and Lluis Gomez. 2023. Transductive Learning for Near-Duplicate Image Detection in Scanned Photo Collections. 17th International Conference on Document Analysis and Recognition.3–17. (LNCS.)
Abstract: This paper presents a comparative study of near-duplicate image detection techniques in a real-world use case scenario, where a document management company is commissioned to manually annotate a collection of scanned photographs. Detecting duplicate and near-duplicate photographs can reduce the time spent on manual annotation by archivists. This real use case differs from laboratory settings as the deployment dataset is available in advance, allowing the use of transductive learning. We propose a transductive learning approach that leverages state-of-the-art deep learning architectures such as convolutional neural networks (CNNs) and Vision Transformers (ViTs). Our approach involves pre-training a deep neural network on a large dataset and then fine-tuning the network on the unlabeled target collection with self-supervised learning. The results show that the proposed approach outperforms the baseline methods in the task of near-duplicate image detection in the UKBench and an in-house private dataset.
Keywords: Image deduplication; Near-duplicate images detection; Transductive Learning; Photographic Archives; Deep Learning
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Francesc Tous, Agnes Borras, Robert Benavente, Ramon Baldrich, Maria Vanrell and Josep Llados. 2002. Textual Descriptors for browsing people by visual appearence. 5è. Congrés Català d’Intel·ligència Artificial CCIA.
Abstract: This paper presents a first approach to build colour and structural descriptors for information retrieval on a people database. Queries are formulated in terms of their appearance that allows to seek people wearing specific clothes of a given colour name or texture. Descriptors are automatically computed by following three essential steps. A colour naming labelling from pixel properties. A region seg- mentation step based on colour properties of pixels combined with edge information. And a high level step that models the region arrangements in order to build clothes structure. Results are tested on large set of images from real scenes taken at the entrance desk of a building.
Keywords: Image retrieval, textual descriptors, colour naming, colour normalization, graph matching.
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