Zobrazeno 1 - 10
of 2 045
pro vyhledávání: '"P. Gadd"'
Autor:
Gadd, Charles, Yau, Christopher
Changes in the number of copies of certain parts of the genome, known as copy number alterations (CNAs), due to somatic mutation processes are a hallmark of many cancers. This genomic complexity is known to be associated with poorer outcomes for pati
Externí odkaz:
http://arxiv.org/abs/2408.12636
Autor:
J. Z. Sippo, I. R. Santos, C. J. Sanders, P. Gadd, Q. Hua, C. E. Lovelock, N. S. Santini, S. G. Johnston, Y. Harada, G. Reithmeir, D. T. Maher
Publikováno v:
Biogeosciences, Vol 17, Pp 4707-4726 (2020)
A massive mangrove dieback event occurred in 2015–2016 along ∼1000 km of pristine coastline in the Gulf of Carpentaria, Australia. Here, we use sediment and wood chronologies to gain insights into geochemical and climatic changes related to this
Externí odkaz:
https://doaj.org/article/735c191c815940bf8f8954cf439c11a7
Autor:
Gadd, Matthew, De Martini, Daniele, Pitt, Luke, Tubby, Wayne, Towlson, Matthew, Prahacs, Chris, Bartlett, Oliver, Jackson, John, Qi, Man, Newman, Paul, Hector, Andrew, Salguero-Gómez, Roberto, Hawes, Nick
We describe a challenging robotics deployment in a complex ecosystem to monitor a rich plant community. The study site is dominated by dynamic grassland vegetation and is thus visually ambiguous and liable to drastic appearance change over the course
Externí odkaz:
http://arxiv.org/abs/2404.10446
This paper adapts a general dataset representation technique to produce robust Visual Place Recognition (VPR) descriptors, crucial to enable real-world mobile robot localisation. Two parallel lines of work on VPR have shown, on one side, that general
Externí odkaz:
http://arxiv.org/abs/2403.09025
This paper is about 3D pose estimation on LiDAR scans with extremely minimal storage requirements to enable scalable mapping and localisation. We achieve this by clustering all points of segmented scans into semantic objects and representing them onl
Externí odkaz:
http://arxiv.org/abs/2403.04755
Autor:
Gadd, Matthew, De Martini, Daniele, Bartlett, Oliver, Murcutt, Paul, Towlson, Matt, Widojo, Matthew, Muşat, Valentina, Robinson, Luke, Panagiotaki, Efimia, Pramatarov, Georgi, Kühn, Marc Alexander, Marchegiani, Letizia, Newman, Paul, Kunze, Lars
There is a growing academic interest as well as commercial exploitation of millimetre-wave scanning radar for autonomous vehicle localisation and scene understanding. Although several datasets to support this research area have been released, they ar
Externí odkaz:
http://arxiv.org/abs/2403.02845
Knowing when a trained segmentation model is encountering data that is different to its training data is important. Understanding and mitigating the effects of this play an important part in their application from a performance and assurance perspect
Externí odkaz:
http://arxiv.org/abs/2402.17653
This work proposes a semantic segmentation network that produces high-quality uncertainty estimates in a single forward pass. We exploit general representations from foundation models and unlabelled datasets through a Masked Image Modeling (MIM) appr
Externí odkaz:
http://arxiv.org/abs/2402.17622
Autor:
Yuan, Jianhao, Sun, Shuyang, Omeiza, Daniel, Zhao, Bo, Newman, Paul, Kunze, Lars, Gadd, Matthew
Publikováno v:
Robotics: Science and Systems (RSS) 2024
We need to trust robots that use often opaque AI methods. They need to explain themselves to us, and we need to trust their explanation. In this regard, explainability plays a critical role in trustworthy autonomous decision-making to foster transpar
Externí odkaz:
http://arxiv.org/abs/2402.10828
Autor:
Gadd, Matthew, Newman, Paul
Radar place recognition often involves encoding a live scan as a vector and matching this vector to a database in order to recognise that the vehicle is in a location that it has visited before. Radar is inherently robust to lighting or weather condi
Externí odkaz:
http://arxiv.org/abs/2401.15380