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Wietske Medema, Jan Adamowski, Christopher Orr, Alison Furber, Arjen Wals and Nicolas Milot
The sustainable governance of water resources relies on processes of multi-stakeholder collaborations and interactions that facilitate the sharing and integration of diverse sources and types of knowledge. In this context, it is essential to fully recogn...
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Wietske Medema, Jan Adamowski, Christopher Orr, Alison Furber, Arjen Wals, Nicolas Milot
Pág. 1 - 22
The sustainable governance of water resources relies on processes of multi-stakeholder collaborations and interactions that facilitate the sharing and integration of diverse sources and types of knowledge. In this context, it is essential to fully recogn...
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Weijun Li, Jintong Liu, Yuxiao Gao, Xinyong Zhang and Jianlai Gu
The task of named entity recognition (NER) is to identify entities in the text and predict their categories. In real-life scenarios, the context of the text is often complex, and there may exist nested entities within an entity. This kind of entity is ca...
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Adriana Burlea-Schiopoiu and Zineb Znagui
Globalization has led to a geographical concentration of economic activities, known as territorialized networks of organizations, especially technopoles. That is why the knowledge process takes on new dimensions and requires a multidimensional and dynami...
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Nikolaos Zafeiropoulos, Pavlos Bitilis, George E. Tsekouras and Konstantinos Kotis
In the realm of Parkinson?s Disease (PD) research, the integration of wearable sensor data with personal health records (PHR) has emerged as a pivotal avenue for patient alerting and monitoring. This study delves into the complex domain of PD patient car...
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Tameem Adel and Mark Levene
We investigate the utility of side information in the context of machine learning and, in particular, in supervised neural networks. Side information can be viewed as expert knowledge, additional to the input, that may come from a knowledge base. Unlike ...
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Aleksandar Ivanovski, Milos Jovanovik, Riste Stojanov and Dimitar Trajanov
In this work, we present a state-of-the-art solution for automatic playlist continuation through a knowledge graph-based recommender system. By integrating representational learning with graph neural networks and fusing multiple data streams, the system ...
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Yasunari Matsuzaka and Ryu Yashiro
Computer vision is a branch of computer science that studies how computers can ?see?. It is a field that provides significant value for advancements in academia and artificial intelligence by processing images captured with a camera. In other words, the ...
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Norbert Fischer, Alexander Hartelt and Frank Puppe
Digitization and transcription of historic documents offer new research opportunities for humanists and are the topics of many edition projects. However, manual work is still required for the main phases of layout recognition and the subsequent optical c...
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Martina Saletta and Claudio Ferretti
Deep neural networks have proven to be able to learn rich internal representations, including for features that can also be used for different purposes than those the networks are originally developed for. In this paper, we are interested in exploring su...
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Shao-Ming Lee and Ja-Ling Wu
Recently, federated learning (FL) has gradually become an important research topic in machine learning and information theory. FL emphasizes that clients jointly engage in solving learning tasks. In addition to data security issues, fundamental challenge...
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Massimo Stella and Yoed N. Kenett
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Alexander Hartelt and Frank Puppe
This paper deals with the effect of exploiting background knowledge for improving an OMR (Optical Music Recognition) deep learning pipeline for transcribing medieval, monophonic, handwritten music from the 12th?14th century, whose usage has been neglecte...
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Rao Mikkilineni
All living beings use autopoiesis and cognition to manage their ?life? processes from birth through death. Autopoiesis enables them to use the specification in their genomes to instantiate themselves using matter and energy transformations. They reproduc...
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Xuhui Zeng, Shu Wang, Yunqiang Zhu, Mengfei Xu and Zhiqiang Zou
The recommendation system is one of the hotspots in the field of artificial intelligence that can be applied to recommend suitable ecological patterns for the countryside. Countryside ecological patterns mean advanced patterns that can be recommended to ...
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Unai Elordi, Chiara Lunerti, Luis Unzueta, Jon Goenetxea, Nerea Aranjuelo, Alvaro Bertelsen and Ignacio Arganda-Carreras
In this paper, we tackle the problem of deploying face recognition (FR) solutions in heterogeneous Internet of Things (IoT) platforms. The main challenges are the optimal deployment of deep neural networks (DNNs) in the high variety of IoT devices (e.g.,...
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Michael S. Vitevitch, Leo Niehorster-Cook and Sasha Niehorster-Cook
In Linguistics and Psycholinguistics, phonotactics refers to the constraints on individual sounds in a given language that restrict how those sounds can be ordered to form words in that language. Previous empirical work in Psycholinguistics demonstrated ...
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Ilias Theodorakopoulos, Foteini Fotopoulou and George Economou
In this work, we propose a mechanism for knowledge transfer between Convolutional Neural Networks via the geometric regularization of local features produced by the activations of convolutional layers. We formulate appropriate loss functions, driving a ?...
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Dario Onorati, Pierfrancesco Tommasino, Leonardo Ranaldi, Francesca Fallucchi and Fabio Massimo Zanzotto
The dazzling success of neural networks over natural language processing systems is imposing an urgent need to control their behavior with simpler, more direct declarative rules. In this paper, we propose Pat-in-the-Loop as a model to control a specific ...
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Martina Neuländtner
Modelling the complex nature of regional knowledge creation is high on the research agenda. It deals with the identification of drivers for regional knowledge creation of different kinds, among them inter-regional networks and agglomeration factors, as w...
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