Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Anders Boesen"'
We present an autoencoder that leverages learned representations to better measure similarities in data space. By combining a variational autoencoder with a generative adversarial network we can use learned feature representations in the GAN discrimi
Externí odkaz:
http://arxiv.org/abs/1512.09300
Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation
Autor:
Hauberg, Søren, Freifeld, Oren, Larsen, Anders Boesen Lindbo, Fisher III, John W., Hansen, Lars Kai
Publikováno v:
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, pp. 342-350, 2016
Data augmentation is a key element in training high-dimensional models. In this approach, one synthesizes new observations by applying pre-specified transformations to the original training data; e.g.~new images are formed by rotating old ones. Curre
Externí odkaz:
http://arxiv.org/abs/1510.02795
Autor:
Kristoffer Weisskirchner Barfod, Maria Swennergren Hansen, Håkon Sandholdt, Anders Boesen, Per Hölmich, Anders Troelsen, Morten Tange Kristensen
Publikováno v:
The Journal of Foot and Ankle Surgery. 61:1098-1102
Elongation of the tendon has been proposed as the most important factor leading to poor outcome after acute Achilles tendon rupture (ATR). The aim of this paper was to investigate if Amlang's ultrasound classification (AmC) or the Copenhagen Achilles
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::78eec54f0f06d1d2c8e16e9a94ed896c
https://doi.org/10.1053/j.jfas.2022.01.028
https://doi.org/10.1053/j.jfas.2022.01.028
Autor:
Jesper Christensen, Anders Boesen Lindbo Larsen, Casper Simonsen, Abigail L. Mackey, Anne Nissen, Klaus Müller, Hanne Bækgaard Larsen, Martin Kaj Fridh, Peter Schmidt-Andersen
Publikováno v:
Bone Marrow Transplantation. 56:2063-2078
The effects of childhood hematopoietic stem cell transplantation (HSCT) on key organs can impair cardiorespiratory fitness, muscle strength, and physical performance. We aimed to provide an overview of childhood HSCT survivors' status on these parame
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::498cc84ee829e3f90306c2bbe82f5f17
https://doi.org/10.1038/s41409-021-01370-2
https://doi.org/10.1038/s41409-021-01370-2
Autor:
Kristoffer Weisskirchner Barfod, Anja Falk Riecke, Anders Boesen, Philip Hansen, Jens Friedrich Maier, Simon Doessing, Anders Troelsen
Publikováno v:
Barfod, K W, Riecke, A F, Boesen, A, Hansen, P, Maier, J F, Doessing, S & Troelsen, A 2018, ' Validity and reliability of an ultrasound measurement of the free length of the Achilles tendon ', Danish Medical Journal, vol. 65, no. 3, A5453 . < http://ugeskriftet.dk/dmj/validity-and-reliability-ultrasound-measurement-free-length-achilles-tendon >
Scopus-Elsevier
Capital Region of Denmark
Scopus-Elsevier
Capital Region of Denmark
INTRODUCTION: Valid length measurements of the different segments of the Achilles tendon are needed in order to investigate if differential elongation of the Achilles tendon takes place after rupture. The purpose of this paper was to present data con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::14ffd70d83ff6e54f06d3c610eb769e6
https://curis.ku.dk/portal/da/publications/validity-and-reliability-of-an-ultrasound-measurement-of-the-free-length-of-the-achilles-tendon(3e74cf6a-59f3-466b-afd8-41a604c3281a).html
https://curis.ku.dk/portal/da/publications/validity-and-reliability-of-an-ultrasound-measurement-of-the-free-length-of-the-achilles-tendon(3e74cf6a-59f3-466b-afd8-41a604c3281a).html
Publikováno v:
IEEE Transactions on Medical Imaging. 33:1573-1580
We present a new method for automatic classification of indirect immunoflourescence images of HEp-2 cells into different staining pattern classes. Our method is based on a new texture measure called shape index histograms that captures second-order i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34afd7a04531eb7ec60d97acc78dd817
https://doi.org/10.1109/tmi.2014.2318434
https://doi.org/10.1109/tmi.2014.2318434
Autor:
Larsen, Anders Boesen Lindbo
Publikováno v:
Larsen, A B L 2016, DeepPy: Pythonic deep learning . DTU Compute-Technical Report-2016, no. 6, Technical University of Denmark, Kgs. Lyngby .
This technical report introduces DeepPy – a deep learning framework built on top of NumPy with GPU acceleration. DeepPy bridges the gap between highperformance neural networks and the ease of development from Python/NumPy. Users with a background i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1202::8bc0f2ccb2c5fcf422db6d8f366d6732
https://orbit.dtu.dk/en/publications/deeppy-pythonic-deep-learning(3f1b6344-9fab-463d-8255-d611fecd03e1).html
https://orbit.dtu.dk/en/publications/deeppy-pythonic-deep-learning(3f1b6344-9fab-463d-8255-d611fecd03e1).html
Autor:
Larsen, Anders Boesen Lindbo
Publikováno v:
Larsen, A B L 2016, Learned image representations for visual recognition . DTU Compute PHD-2016, no. 418, Technical University of Denmark, Kgs. Lyngby .
This thesis addresses the problem of extracting image structures for representing images effectively in order to solve visual recognition tasks. Problems from diverse research areas (medical imaging, material science and food processing) have motivat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1202::a5976dfe976bf35d22970d42974d57f7
https://orbit.dtu.dk/en/publications/learned-image-representations-for-visual-recognition(725cb374-eb72-4567-9c07-adee3bb50436).html
https://orbit.dtu.dk/en/publications/learned-image-representations-for-visual-recognition(725cb374-eb72-4567-9c07-adee3bb50436).html
Publikováno v:
Engineering Computations. 29:65-82
Purpose – The purpose of this paper is to determine the magnitude and spatial distribution of the heat transfer coefficient between the workpiece and the backing plate in a friction stir welding process using inverse modelling. Design/methodology/a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ff7566ec6dbae49ae2c171a2b8eb8e9
https://doi.org/10.1108/02644401211190573
https://doi.org/10.1108/02644401211190573
Autor:
F. Boray Tek, Stefan M. Willems, Bogdan J. Matuszewski, Josien P. W. Pluim, Satoshi Kondo, Paul J. van Diest, Anders Boesen Lindbo Larsen, Fabio A. González, Violet Snell, Evdokia Arkoumani, Josef Kittler, Alessandro Giusti, Jacob S. Vestergaard, Adnan Mujahid Khan, Thomas Walter, Luca Maria Gambardella, Mitko Veta, Ching-Wei Wang, Frédéric Precioso, Anant Madabhushi, Max A. Viergever, Teofilo de Campos, Miangela M. Lacle, Anders Bjorholm Dahl, Haibo Wang, Angel Cruz-Roa, Dan Ciresan, Nasir M. Rajpoot, Jürgen Schmidhuber
Publikováno v:
Medical Image Analysis
Medical Image Analysis, Elsevier, 2015, 20 (1), pp.237-248. ⟨10.1016/j.media.2014.11.010⟩
Medical image analysis
Medical Image Analysis, 20(1), 237. Elsevier
Veta, M, van Diest, P J, Willems, S M, Wang, H, Madabhushi, A, Cruz-Roa, A, Gonzalez, F, Larsen, A B L, Vestergaard, J S, Dahl, A B, Ciresan, D C, Schmidhuber, J, Giusti, A, Gambardella, L M, Tek, F B, Walter, T, Wang, C-W, Kondo, S, Matuszewski, B J, Precioso, F, Snell, V, Kittler, J, de Campos, T E, Khan, A M, Rajpoot, N M, Arkoumani, E, Lacle, M M, Viergever, M A & Pluim, J P W 2015, ' Assessment of algorithms for mitosis detection in breast cancer histopathology images ', Medical Image Analysis, vol. 20, no. 1, pp. 237-248 . https://doi.org/10.1016/j.media.2014.11.010
Medical Image Analysis, 20(1), 237-248. Elsevier
Medical Image Analysis, Elsevier, 2015, 20 (1), pp.237-248. ⟨10.1016/j.media.2014.11.010⟩
Medical image analysis
Medical Image Analysis, 20(1), 237. Elsevier
Veta, M, van Diest, P J, Willems, S M, Wang, H, Madabhushi, A, Cruz-Roa, A, Gonzalez, F, Larsen, A B L, Vestergaard, J S, Dahl, A B, Ciresan, D C, Schmidhuber, J, Giusti, A, Gambardella, L M, Tek, F B, Walter, T, Wang, C-W, Kondo, S, Matuszewski, B J, Precioso, F, Snell, V, Kittler, J, de Campos, T E, Khan, A M, Rajpoot, N M, Arkoumani, E, Lacle, M M, Viergever, M A & Pluim, J P W 2015, ' Assessment of algorithms for mitosis detection in breast cancer histopathology images ', Medical Image Analysis, vol. 20, no. 1, pp. 237-248 . https://doi.org/10.1016/j.media.2014.11.010
Medical Image Analysis, 20(1), 237-248. Elsevier
The proliferative activity of breast tumors, which is routinely estimated by counting of mitotic figures in hematoxylin and eosin stained histology sections, is considered to be one of the most important prognostic markers. However, mitosis counting
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8788284850ba5f95b3831d26d69e76ce
https://dspace.library.uu.nl/handle/1874/331335
https://dspace.library.uu.nl/handle/1874/331335