Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Asenov, Martin"'
Autor:
Darlow, Luke, Deng, Qiwen, Hassan, Ahmed, Asenov, Martin, Singh, Rajkarn, Joosen, Artjom, Barker, Adam, Storkey, Amos
It is challenging to scale time series forecasting models such that they forecast accurately for multiple distinct domains and datasets, all with potentially different underlying collection procedures (e.g., sample resolution), patterns (e.g., period
Externí odkaz:
http://arxiv.org/abs/2407.17880
Autor:
Joosen, Artjom, Hassan, Ahmed, Asenov, Martin, Singh, Rajkarn, Darlow, Luke, Wang, Jianfeng, Barker, Adam
Publikováno v:
SoCC '23: Proceedings of the 2023 ACM Symposium on Cloud Computing, October 2023, Pages 443-458
This paper releases and analyzes two new Huawei cloud serverless traces. The traces span a period of over 7 months with over 1.4 trillion function invocations combined. The first trace is derived from Huawei's internal workloads and contains detailed
Externí odkaz:
http://arxiv.org/abs/2312.10127
Autor:
Tiseo, Carlo, Rouxel, Quentin, Asenov, Martin, Babarahmati, Keyhan Kouhkiloui, Ramamoorthy, Subramanian, Li, Zhibin, Mistry, Michael
Medical robotics can help improve and extend the reach of healthcare services. A major challenge for medical robots is the complex physical interaction between the robot and the patients which is required to be safe. This work presents the preliminar
Externí odkaz:
http://arxiv.org/abs/2206.09906
This paper introduces V-SysId, a novel method that enables simultaneous keypoint discovery, 3D system identification, and extrinsic camera calibration from an unlabeled video taken from a static camera, using only the family of equations of motion of
Externí odkaz:
http://arxiv.org/abs/2109.05928
Autor:
Asenov, Martin, Burke, Michael, Angelov, Daniel, Davchev, Todor, Subr, Kartic, Ramamoorthy, Subramanian
Videos provide a rich source of information, but it is generally hard to extract dynamical parameters of interest. Inferring those parameters from a video stream would be beneficial for physical reasoning. Robots performing tasks in dynamic environme
Externí odkaz:
http://arxiv.org/abs/1907.06422
Sensors are routinely mounted on robots to acquire various forms of measurements in spatio-temporal fields. Locating features within these fields and reconstruction (mapping) of the dense fields can be challenging in resource-constrained situations,
Externí odkaz:
http://arxiv.org/abs/1901.09608
Autor:
Asenov, Martin
Publikováno v:
Trends in Regional Development and Security Management. :129-134
Externí odkaz:
https://www.ceeol.com/search/chapter-detail?id=838255
Autor:
Nikolov, Georgi, Pavlov, Georgi, Poudin, Konstantin, Petrov, Kamen, Ivanov, Jivko, Mironova, Nadia, Tsonkov, Nikolai, Kaneva, Aglika, Petkova, Ivelina, Lyubomirova, Veselina, Tanakov, Nikola, Iliev, Petkan, Berberova-Valcheva, Cvetelina, Bozmarova, Adela, Tsankova, Gergana, Stoyanov, Zahariy, Asenov, Martin, Boteva, Maria, Kazakova, Mariya, Angelov, Rumen, Penkova, Tzvetomira, Botseva, Desislava, Kochev, Ivan, Kolarov, Ruslan, Tsolovska, Anna, Tsolov, Georgi, Sakollari, Valbona, Kostić, Dragan, Simonović, Aleksandar
Externí odkaz:
https://www.ceeol.com/search/book-detail?id=838098
Autor:
Asenov, Martin Andreev
Robotic systems have enjoyed significant adoption in industrial and field applications in structured environments, where clear specifications of the task and observations are available. Deploying robots in unstructured and dynamic environments remain
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::632e4ef116e7030aeeb65ac6260e5844
Publikováno v:
Jaques, M, Asenov, M, Burke, M & Hospedales, T M 2022, Vision-based system identification and 3D keypoint discovery using dynamics constraints . in R Firoozi, N Mehr, E Yel, R Antonova, J Bohg, M Schwager & M Kochendorfer (eds), Proceedings of The 4th Annual Learning for Dynamics and Control Conference : Volume 168: Learning for Dynamics and Control Conference, 23-24 June 2022, Stanford University, Stanford, CA, USA . vol. 168, pp. 316-329, 4th Annual Learning for Dynamics & Control Conference, Stanford, California, United States, 23/06/22 . < https://proceedings.mlr.press/v168/jaques22a.html >
This paper introduces V-SysId, a novel method that enables simultaneous keypoint discovery, 3D system identification, and extrinsic camera calibration from an unlabeled video taken from a static camera, using only the family of equations of motion of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3094::e147a3517fff7475f8e3355329388e93
https://hdl.handle.net/20.500.11820/6699363c-606e-479c-a5cd-b5a2ea3c6016
https://hdl.handle.net/20.500.11820/6699363c-606e-479c-a5cd-b5a2ea3c6016