Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Ian Truckell"'
The need for training and benchmark datasets for convolutional neural networks in flood applications
Publikováno v:
Hydrology Research, Vol 53, Iss 6, Pp 795-806 (2022)
Flood-related image datasets from social media, smartphones, CCTV cameras, and unmanned aerial vehicles (UAVs) present valuable data for the management of flood risk, and particularly for the application of modern convolutional neural networks (CNNs)
Externí odkaz:
https://doaj.org/article/34bc4d3e5ff044229215189b423e50f0
Autor:
Rakhee Ramachandran, Yadira Bajón Fernández, Ian Truckell, Carlos Constantino, Richard Casselden, Paul Leinster, Mónica Rivas Casado
Publikováno v:
Remote Sensing, Vol 15, Iss 7, p 1912 (2023)
With the increase in rainfall intensity, population, and urbanised areas, surface water flooding (SWF) is an increasing concern impacting properties, businesses, and human lives. Previous studies have shown that microtopography significantly influenc
Externí odkaz:
https://doaj.org/article/8f3535756e08453ea7db99daa6aae4b6
Publikováno v:
International Journal of Digital Earth, Vol 13, Iss 8, Pp 899-914 (2020)
We propose a method for spatial downscaling of Landsat 8-derived LST maps from 100(30 m) resolution down to 2–4 m with the use of the Multiple Adaptive Regression Splines (MARS) models coupled with very high resolution auxiliary data derived from h
Externí odkaz:
https://doaj.org/article/639d7903cab74e9e88a6b0a58e33e742
Publikováno v:
Remote Sensing, Vol 13, Iss 19, p 3913 (2021)
Timely clearing-up interventions are essential for effective recovery of flood-damaged housing, however, time-consuming door-to-door inspections for insurance purposes need to take place before major repairs can be done to adequately assess the losse
Externí odkaz:
https://doaj.org/article/cdebe139ea904d5d9b67aaf848ba90b2
Autor:
Liz Varga, Lauren McMillan, Stephen Hallett, Tom Russell, Luke Smith, Ian Truckell, Andrey Postnikov, Sunil Rodger, Noel Vizcaino, Bethan Perkins, Brian Matthews, Nik Lomax
Publikováno v:
Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction. :1-10
The creation and use of ontologies has become increasingly relevant for complex systems in recent years. This is because of the growing number of use of cases that rely on real-world integration of disparate systems, the need for semantic congruence
The need for training and benchmark datasets for convolutional neural networks in flood applications
Flood-related image datasets from social media, smartphones, CCTV cameras, and unmanned aerial vehicles (UAVs) present valuable data for the management of flood risk, and particularly for the application of modern convolutional neural networks (CNNs)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::32f261e66395102a1d353cbefd7fabaa
https://dspace.lib.cranfield.ac.uk/handle/1826/18188
https://dspace.lib.cranfield.ac.uk/handle/1826/18188