Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Hedvig Kjellström"'
Autor:
Ci Li, Ylva Mellbin, Johanna Krogager, Senya Polikovsky, Martin Holmberg, Nima Ghorbani, Michael J. Black, Hedvig Kjellström, Silvia Zuffi, Elin Hernlund
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-15 (2024)
Abstract Studies of quadruped animal motion help us to identify diseases, understand behavior and unravel the mechanics behind gaits in animals. The horse is likely the best-studied animal in this aspect, but data capture is challenging and time-cons
Externí odkaz:
https://doaj.org/article/70a01c7d715c48709fbdf958819d1a8f
Autor:
Andrew Karvonen, Vladimir Cvetkovic, Pawel Herman, Karl Johansson, Hedvig Kjellström, Marco Molinari, Mikael Skoglund
Publikováno v:
Urban Transformations, Vol 3, Iss 1, Pp 1-13 (2021)
Highlights The New Urban Science leverages digital tools and techniques to develop new knowledge that can inform urban development processes. Interdisciplinary and transdisciplinary approaches are critical to expanding and enhancing digital modes of
Externí odkaz:
https://doaj.org/article/e110835c225e454da03b5428409edb7d
Autor:
Felix Järemo Lawin, Anna Byström, Christoffer Roepstorff, Marie Rhodin, Mattias Almlöf, Mudith Silva, Pia Haubro Andersen, Hedvig Kjellström, Elin Hernlund
Publikováno v:
Animals, Vol 13, Iss 3, p 390 (2023)
Computer vision is a subcategory of artificial intelligence focused on extraction of information from images and video. It provides a compelling new means for objective orthopaedic gait assessment in horses using accessible hardware, such as a smartp
Externí odkaz:
https://doaj.org/article/3b05461a330a4bdd864617dcb5c557fc
Publikováno v:
PLoS ONE, Vol 17, Iss 3 (2022)
Orthopedic disorders are common among horses, often leading to euthanasia, which often could have been avoided with earlier detection. These conditions often create varying degrees of subtle long-term pain. It is challenging to train a visual pain re
Externí odkaz:
https://doaj.org/article/6487f8d65755447caf727162a9a61e91
Autor:
Patrik Jonell, Birger Moëll, Krister Håkansson, Gustav Eje Henter, Taras Kucherenko, Olga Mikheeva, Göran Hagman, Jasper Holleman, Miia Kivipelto, Hedvig Kjellström, Joakim Gustafson, Jonas Beskow
Publikováno v:
Frontiers in Computer Science, Vol 3 (2021)
Non-invasive automatic screening for Alzheimer’s disease has the potential to improve diagnostic accuracy while lowering healthcare costs. Previous research has shown that patterns in speech, language, gaze, and drawing can help detect early signs
Externí odkaz:
https://doaj.org/article/0833e68562ee4a96a451e97c15df2cdc
Publikováno v:
Patterns, Vol 1, Iss 8, Pp 100143- (2020)
Summary: An essential task for computer vision-based assistive technologies is to help visually impaired people to recognize objects in constrained environments, for instance, recognizing food items in grocery stores. In this paper, we introduce a no
Externí odkaz:
https://doaj.org/article/390317ce708748d59c00258da8a72256
Autor:
Pia Haubro Andersen, Sofia Broomé, Maheen Rashid, Johan Lundblad, Katrina Ask, Zhenghong Li, Elin Hernlund, Marie Rhodin, Hedvig Kjellström
Publikováno v:
Animals, Vol 11, Iss 6, p 1643 (2021)
Automated recognition of human facial expressions of pain and emotions is to a certain degree a solved problem, using approaches based on computer vision and machine learning. However, the application of such methods to horses has proven difficult. M
Externí odkaz:
https://doaj.org/article/3d661063200d4d2283c186fab3b06cb9
Publikováno v:
Journal of Computational and Graphical Statistics. :1-9
Autor:
Sofia Broomé, Marcelo Feighelstein, Anna Zamansky, Gabriel Carreira Lencioni, Pia Haubro Andersen, Francisca Pessanha, Marwa Mahmoud, Hedvig Kjellström, Albert Ali Salah
Advances in animal motion tracking and pose recognition have been a game changer in the study of animal behavior. Recently, an increasing number of works go ‘deeper’ than tracking, and address automated recognition of animals’ internal states s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e4dc0396a01324e12f283c53b173a29
https://pub.epsilon.slu.se/30105/
https://pub.epsilon.slu.se/30105/
Autor:
Patrik Jonell, Hedvig Kjellström, Gustav Eje Henter, Rajmund Nagy, Taras Kucherenko, Michael Neff
Publikováno v:
IVA
We propose a new framework for gesture generation, aiming to allow data-driven approaches to produce more semantically rich gestures. Our approach first predicts whether to gesture, followed by a prediction of the gesture properties. Those properties
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a42dfd31a5db280591b7bf4dfbffd172
http://arxiv.org/abs/2106.14736
http://arxiv.org/abs/2106.14736