Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Tien Huu Do"'
Publikováno v:
IEEE Access, Vol 9, Pp 130042-130054 (2021)
Fake news is a serious problem, which has received considerable attention from both industry and academic communities. Over the past years, many fake news detection approaches have been introduced, and most of the existing methods rely on either news
Externí odkaz:
https://doaj.org/article/2b28d7f017554d69980b2d7d4f3a5093
Autor:
Xuening Qin, Tien Huu Do, Jelle Hofman, Esther Rodrigo Bonet, Valerio Panzica La Manna, Nikos Deligiannis, Wilfried Philips
Publikováno v:
Remote Sensing, Vol 14, Iss 11, p 2613 (2022)
Urban air quality mapping has been widely applied in urban planning, air pollution control and personal air pollution exposure assessment. Urban air quality maps are traditionally derived using measurements from fixed monitoring stations. Due to high
Externí odkaz:
https://doaj.org/article/90d4718df6394cf991f2e5a38fa3d749
Autor:
Esther Rodrigo Bonet, Tien Huu Do, Xuening Qin, Jelle Hofman, Valerio Panzica La Manna, Wilfried Philips, Nikos Deligiannis
Publikováno v:
2022 30th European Signal Processing Conference (EUSIPCO).
Publikováno v:
IEEE Access, Vol 9, Pp 130042-130054 (2021)
Fake news is a serious problem, which has received considerable attention from both industry and academic communities. Over the past years, many fake news detection approaches have been introduced, and most of the existing methods rely on either news
Akademický článek
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Autor:
Tien Huu Do, Jelle Hofman, Nikos Deligiannis, Evaggelia Tsiligianni, Xuening Qin, Valerio Panzica La Manna, Wilfried Philips
Publikováno v:
IEEE Internet of Things Journal. 7:8943-8955
Internet-of-Things (IoT) technologies incorporate a large number of different sensing devices and communication technologies to collect a large amount of data for various applications. Smart cities employ IoT infrastructures to build services useful
Autor:
Esther Rodrigo Bonet, Tien Huu Do, Xuening Qin, Jelle Hofman, Valerio Panzica La Manna, Wilfried Philips, Nikos Deligiannis
Graph neural networks (GNNs) have proven their ability in modelling graph-structured data in diverse domains, including natural language processing and computer vision. However, like other deep learning models, the lack of explainability is becoming
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::527de0a15be8ef86d9610842ef88e2de
https://biblio.vub.ac.be/vubir/explaining-graph-neural-networks-with-topologyaware-node-selection-application-in-air-quality-inference(a869a6a8-357a-4568-bff6-907bbca038f7).html
https://biblio.vub.ac.be/vubir/explaining-graph-neural-networks-with-topologyaware-node-selection-application-in-air-quality-inference(a869a6a8-357a-4568-bff6-907bbca038f7).html
Autor:
Esther Rodrigo, Wilfried Philips, Valerio La Manna Panzica, Tien Huu Do, Nikos Deligiannis, Xuening Qin, Jelle Hofman
Publikováno v:
ICIAI
The spatial heterogeneity and temporal variability of air pollution in urban environments make air quality inference for fine-grained air pollution monitoring extremely challenging. Most of the existing work estimates the air quality using sparse mea
Graph convolutional neural networks (GCNNs) have received much attention recently, owing to their capability in handling graph-structured data. Among the existing GCNNs, many methods can be viewed as instances of a neural message passing motif; featu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::73811ac5bcce6231eb59fa83f220030a
https://doi.org/10.1016/j.eswa.2021.114711
https://doi.org/10.1016/j.eswa.2021.114711
Autor:
Nikos Deligiannis, Tien Huu Do, Valerio Panzica La Manna, Esther Rodrigo, Jelle Hofman, Wilfried Philips, Xuening Qin, Martha E. Nikolaou
Publikováno v:
Pattern Recognition. ICPR International Workshops and Challenges ISBN: 9783030687793
ICPR Workshops (6)
ICPR Workshops (6)
Air quality monitoring in heterogeneous cities is challenging as a high resolution in both space and time is required to accurately assess population exposure. As regulatory monitoring networks are sparse due to high investment and maintenance costs,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6443a7f53c8eae127fc2e7e0128c9219
https://doi.org/10.1007/978-3-030-68780-9_14
https://doi.org/10.1007/978-3-030-68780-9_14