Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Mike E. Davies"'
Autor:
Ahmed Karam Eldaly, Ming Fang, Angela Di Fulvio, Stephen McLaughlin, Mike E. Davies, Yoann Altmann, Yves Wiaux
Publikováno v:
Journal of Imaging, Vol 7, Iss 10, p 212 (2021)
In this paper, we address the problem of activity estimation in passive gamma emission tomography (PGET) of spent nuclear fuel. Two different noise models are considered and compared, namely, the isotropic Gaussian and the Poisson noise models. The p
Externí odkaz:
https://doaj.org/article/62db7872ceb048bc898a50710489d87c
Publikováno v:
Chen, D, Tachella, J & Davies, M E 2022, Robust Equivariant Imaging: a fully unsupervised framework for learning to image from noisy and partial measurements . in 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5637-5646, IEEE/CVF Conference on Computer Vision and Pattern Recognition 2022, New Orleans, Louisiana, United States, 19/06/22 . https://doi.org/10.1109/CVPR52688.2022.00556
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Deep networks provide state-of-the-art performance in multiple imaging inverse problems ranging from medical imaging to computational photography. However, most existing networks are trained with clean signals which are often hard or impossible to ob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab6ec4c3020a30354434cff595d6b378
https://hdl.handle.net/20.500.11820/9d5c06ac-52f5-466b-bce0-87bcf85a4c5a
https://hdl.handle.net/20.500.11820/9d5c06ac-52f5-466b-bce0-87bcf85a4c5a
Publikováno v:
Sun, M, Davies, M E, Proudler, I & Hopgood, J R 2022, ' Adaptive Kernel Kalman Filter based Belief Propagation Algorithm for Maneuvering Multi-target Tracking ', IEEE Signal Processing Letters, vol. 29, pp. 1452-1456 . https://doi.org/10.1109/LSP.2022.3184534
This letter incorporates the adaptive kernel Kalman filter (AKKF) into the belief propagation (BP) algorithm for Multi-target tracking (MTT) in single-sensor systems. The algorithm is capable of tracking an unknown and time-varying number of targets,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a446439e76adc17c3b9e7c1c61eaa33e
https://hdl.handle.net/20.500.11820/8dc2da5a-82ad-41fa-8f0d-fc4b6623123a
https://hdl.handle.net/20.500.11820/8dc2da5a-82ad-41fa-8f0d-fc4b6623123a
This volume contains the papers presented at the 7th International Conference on Independent Component Analysis (ICA) and Source Separation held in L- don, 9–12 September 2007, at Queen Mary, University of London. Independent Component Analysis and
Publikováno v:
Physics in Medicine & Biology; Nov2018, Vol. 63 Issue 22, p1-1, 1p
Publikováno v:
Physics in Medicine & Biology; 11/21/2017, Vol. 62 Issue 22, p1-1, 1p
Autor:
Pierre Comon, Marc Castella
Publikováno v:
Independent Component Analysis and Signal Separation ISBN: 9783540744931
ICA
ICA 2007
7th International Conference on Independent Component Analysis and Signal Separation
7th International Conference on Independent Component Analysis and Signal Separation, Sep 2007, London, United Kingdom. pp.9-16
ICA
ICA 2007
7th International Conference on Independent Component Analysis and Signal Separation
7th International Conference on Independent Component Analysis and Signal Separation, Sep 2007, London, United Kingdom. pp.9-16
International audience; This paper deals with the problem of Blind Source Separation. Contrary to the vast majority of works, we do not assume the statistical independence between sources and explicitly consider that they are dependent. We introduce
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::49d129749569f1c1fe79c3bd9b27439b
https://doi.org/10.1007/978-3-540-74494-8_2
https://doi.org/10.1007/978-3-540-74494-8_2
Publikováno v:
Independent Component Analysis and Signal Separation
7th International Conference of Independent Component Analysis and Signal Separation, ICA 2007
7th International Conference of Independent Component Analysis and Signal Separation, ICA 2007, Sep 2007, London, United Kingdom. pp.129-136, ⟨10.1007/978-3-540-74494-8_17⟩
Independent Component Analysis and Signal Separation ISBN: 9783540744931
ICA
7th International Conference of Independent Component Analysis and Signal Separation, ICA 2007
7th International Conference of Independent Component Analysis and Signal Separation, ICA 2007, Sep 2007, London, United Kingdom. pp.129-136, ⟨10.1007/978-3-540-74494-8_17⟩
Independent Component Analysis and Signal Separation ISBN: 9783540744931
ICA
Best Paper; International audience; Renyi's entropy-based criterion has been proposed as an objective function for independent component analysis because of its relationship with Shannon's entropy and its computational advantages in specific cases. T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::932d34937484f133e9c4dfb52ec072ea
https://hal.archives-ouvertes.fr/hal-00853922
https://hal.archives-ouvertes.fr/hal-00853922
Autor:
D. T. Pham
Publikováno v:
Independent Component Analysis and Signal Separation
ICA 2007-7th International Conference on Independent Component Analysis ans Signal Separation
ICA 2007-7th International Conference on Independent Component Analysis ans Signal Separation, Sep 2007, London, United Kingdom. pp.244-251, ⟨10.1007/978-3-540-74494-8_31⟩
Independent Component Analysis and Signal Separation ISBN: 9783540744931
ICA
ICA 2007-7th International Conference on Independent Component Analysis ans Signal Separation
ICA 2007-7th International Conference on Independent Component Analysis ans Signal Separation, Sep 2007, London, United Kingdom. pp.244-251, ⟨10.1007/978-3-540-74494-8_31⟩
Independent Component Analysis and Signal Separation ISBN: 9783540744931
ICA
International audience; This paper introduces an extension of an earlier method of the author for separating stationary sources, based on the joint approximated diagonalization of interspectral matrices, to the case of cyclostationary sources, to tak
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::548e637c6eef7b46768f724fadc659c1
https://hal.archives-ouvertes.fr/hal-00853921
https://hal.archives-ouvertes.fr/hal-00853921