Zobrazeno 1 - 10
of 60
pro vyhledávání: '"Carl Henrik Ek"'
Publikováno v:
Mathematics, Vol 11, Iss 2, p 380 (2023)
The close relation between spatial kinematics and line geometry has been proven to be fruitful in surface detection and reconstruction. However, methods based on this approach are limited to simple geometric shapes that can be formulated as a linear
Externí odkaz:
https://doaj.org/article/5ae406e378124b4e8966e0dbf5083912
Autor:
Yasemin Bekiroglu, Mårten Björkman, Gabriela Zarzar Gandler, Johannes Exner, Carl Henrik Ek, Danica Kragic
Publikováno v:
Data in Brief, Vol 30, Iss , Pp 105335- (2020)
Representing 3D geometry for different tasks, e.g. rendering and reconstruction, is an important goal in different fields, such as computer graphics, computer vision and robotics. Robotic applications often require perception of object shape informat
Externí odkaz:
https://doaj.org/article/5d1df00637434e559c9d7d57bd991bcf
MotivationThere exists a range of different quantification frameworks to estimate the synergistic effect of drug combinations. The diversity and disagreement in estimates make it challenging to determine which combinations from a large drug screening
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::31d6dcadc64128b1321712bee9a87948
https://doi.org/10.1101/2023.01.24.524900
https://doi.org/10.1101/2023.01.24.524900
Publikováno v:
Neurocomputing. 416:352-359
In this paper, we present a model-based reinforcement learning system where the transition model is treated in a Bayesian manner. The approach naturally lends itself to exploit expert knowledge by introducing priors to impose structure on the underly
Publikováno v:
ICRA
This paper presents a two-stage method to perform trajectory optimisation in multimodal dynamical systems with unknown nonlinear stochastic transition dynamics. The method finds trajectories that remain in a preferred dynamics mode where possible and
Publikováno v:
PLoS ONE, Vol 9, Iss 2, p e89184 (2014)
Computational methods have started playing a significant role in semantic analysis. One particularly accessible area for developing good computational methods for linguistic semantics is in color naming, where perceptual dissimilarity measures provid
Externí odkaz:
https://doaj.org/article/2e3343051d6c41b0bfba225296e2e249
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030461461
ECML/PKDD (2)
ECML/PKDD (2)
The data association problem is concerned with separating data coming from different generating processes, for example when data comes from different data sources, contain significant noise, or exhibit multimodality. We present a fully Bayesian appro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1d410569786339ee9c1da73c1f45f14
https://doi.org/10.1007/978-3-030-46147-8_33
https://doi.org/10.1007/978-3-030-46147-8_33
Publikováno v:
Computer Vision – ACCV 2018 ISBN: 9783030208691
ACCV (4)
ACCV (4)
The shape of an object is an important characteristic for many vision problems such as segmentation, detection and tracking. Being independent of appearance, it is possible to generalize to a large range of objects from only small amounts of data. Ho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::88118489535126cc6bd65f1707805fc4
https://doi.org/10.1007/978-3-030-20870-7_1
https://doi.org/10.1007/978-3-030-20870-7_1
Publikováno v:
Robotics and Autonomous Systems. 126:103433
Inferring and representing three-dimensional shapes is an important part of robotic perception. However, it is challenging to build accurate models of novel objects based on real sensory data, because observed data is typically incomplete and noisy.
Publikováno v:
FG
Dissimilarity measures are often used as a proxy or a handle to reason about data. This can be problematic, as the data representation is often a consequence of the capturing process or how the data is visualized, rather than a reflection of the sema