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pro vyhledávání: '"Krippahl, Ludwig"'
Autor:
Ferreira, João, Lavado, Diogo, Gonçalves, Ricardo, Knorr, Matthias, Krippahl, Ludwig, Leite, João
With the constant increase of available data in various domains, such as the Internet of Things, Social Networks or Smart Cities, it has become fundamental that agents are able to process and reason with such data in real time. Whereas reasoning over
Externí odkaz:
http://arxiv.org/abs/2106.08457
Autor:
Ferreira, Ricardo, Lopes, Carolina, Gonçalves, Ricardo, Knorr, Matthias, Krippahl, Ludwig, Leite, João
The amount of information produced, whether by newspapers, blogs and social networks, or by monitoring systems, is increasing rapidly. Processing all this data in real-time, while taking into consideration advanced knowledge about the problem domain,
Externí odkaz:
http://arxiv.org/abs/2106.08452
The Explainable Abstract Trains Dataset is an image dataset containing simplified representations of trains. It aims to provide a platform for the application and research of algorithms for justification and explanation extraction. The dataset is acc
Externí odkaz:
http://arxiv.org/abs/2012.12115
Machine Learning (ML) has been increasingly used to aid humans to make better and faster decisions. However, non-technical humans-in-the-loop struggle to comprehend the rationale behind model predictions, hindering trust in algorithmic decision-makin
Externí odkaz:
http://arxiv.org/abs/2012.01932
Publikováno v:
In Knowledge-Based Systems 5 December 2022 257
Botnets represent a global problem and are responsible for causing large financial and operational damage to their victims. They are implemented with evasion in mind, and aim at hiding their architecture and authors, making them difficult to detect i
Externí odkaz:
http://arxiv.org/abs/1410.8747
Autor:
Ferreira, Jo��o, Lavado, Diogo, Gon��alves, Ricardo, Knorr, Matthias, Krippahl, Ludwig, Leite, Jo��o
With the constant increase of available data in various domains, such as the Internet of Things, Social Networks or Smart Cities, it has become fundamental that agents are able to process and reason with such data in real time. Whereas reasoning over
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::12ad39e230921c33385331d559ddf807
http://arxiv.org/abs/2106.08457
http://arxiv.org/abs/2106.08457
Funding: This work was funded by the project “MATISSE: A machine learning-based forecasting system for shellfish safety” (DSAIPA/DS/0026/2019). The work was also supported by national funds through Fundação para a Ciência e a Tecnologia (FCT)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1437::5f8a974b7807979b962a23e575b2bada
https://hdl.handle.net/10362/125029
https://hdl.handle.net/10362/125029
Autor:
Saraiva, Bruno M., Krippahl, Ludwig, Filipe, Sérgio R., Henriques, Ricardo, Pinho, Mariana G.
Publikováno v:
Biological Imaging
Fluorescence microscopy is a critical tool for cell biology studies on bacterial cell division and morphogenesis. Because the analysis of fluorescence microscopy images evolved beyond initial qualitative studies, numerous images analysis tools were d
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