Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Pavlo Molchanov"'
Publikováno v:
Active and Passive Electronic Components, Vol 23, Iss 1, Pp 25-36 (2000)
The active elements based on dynamic transistor negatrons (circuits with negative active differential resistance) are introduced. The principles of dynamic transistor negatrons simulation has been developed on the basis of non-linear charge model. Pa
Externí odkaz:
https://doaj.org/article/072b6374e28e4a9a8c58656a20b89199
Publikováno v:
Active and Passive Electronic Components, Vol 23, Iss 3, Pp 115-129 (2000)
The simulation principles of monolithic microwave dynamic transistor negatrons (circuits with negative differential active resistance) are introduced. The non-linear model has been developed on the basis of non-linear charge model. The equivalent cir
Externí odkaz:
https://doaj.org/article/972e494f2e8843cf92c80a0eabbf6f3d
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d6b74539784bf5cde9d30b458759777
https://doi.org/10.1109/cvpr52688.2022.01054
https://doi.org/10.1109/cvpr52688.2022.01054
Autor:
Ali Hatamizadeh, Hongxu Yin, Pavlo Molchanov, Andriy Myronenko, Wenqi Li, Prerna Dogra, Andrew Feng, Mona G. Flores, Jan Kautz, Daguang Xu, Holger R. Roth
Federated learning (FL) allows the collaborative training of AI models without needing to share raw data. This capability makes it especially interesting for healthcare applications where patient and data privacy is of utmost concern. However, recent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::03386586ccc3d187beee4b0bbbd9c540
http://arxiv.org/abs/2202.06924
http://arxiv.org/abs/2202.06924
Autor:
Eugene Vorontsov, Pavlo Molchanov, Matej Gazda, Christopher Beckham, Jan Kautz, Samuel Kadoury
Publikováno v:
Medical image analysis. 82
An important challenge and limiting factor in deep learning methods for medical imaging segmentation is the lack of available of annotated data to properly train models. For the specific task of tumor segmentation, the process entails clinicians labe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd4be605cae7f21fd7a53217573a739b
https://pubmed.ncbi.nlm.nih.gov/36208571
https://pubmed.ncbi.nlm.nih.gov/36208571
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031197741
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fb995125d7c0a28cd835dfa5435cbd72
https://doi.org/10.1007/978-3-031-19775-8_9
https://doi.org/10.1007/978-3-031-19775-8_9
Autor:
Ali Hatamizadeh, Hongxu Yin, Pavlo Molchanov, Andriy Myronenko, Wenqi Li, Prerna Dogra, Andrew Feng, Mona Flores, Jan Kautz, Daguang Xu, Holger Roth
Federated learning (FL) allows the collaborative training of AI models without needing to share raw data. This capability makes it especially interesting for healthcare applications where patient and data privacy is of utmost concern. However, recent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e4433c528ad67f0b4ebe317cf0550cf
https://doi.org/10.21203/rs.3.rs-1147182/v1
https://doi.org/10.21203/rs.3.rs-1147182/v1
Autor:
Abdulrahman Mahmoud, Siva Kumar Sastry Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Stephen W. Keckler
Publikováno v:
2021 IEEE 32nd International Symposium on Software Reliability Engineering (ISSRE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e6384e8fb7afcf899941318981fb7692
https://doi.org/10.1109/issre52982.2021.00025
https://doi.org/10.1109/issre52982.2021.00025
Autor:
Yashraj S. Narang, Jonathan Tremblay, Wei Yang, Ankur Handa, Yu-Wei Chao, Dieter Fox, Stan Birchfield, Karl Van Wyk, Umar Iqbal, Jan Kautz, Yu Xiang, Pavlo Molchanov
Publikováno v:
CVPR
We introduce DexYCB, a new dataset for capturing hand grasping of objects. We first compare DexYCB with a related one through cross-dataset evaluation. We then present a thorough benchmark of state-of-the-art approaches on three relevant tasks: 2D ob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::233d6196f27127beecfff6c5d1d7a40a
https://doi.org/10.1109/cvpr46437.2021.00893
https://doi.org/10.1109/cvpr46437.2021.00893
Autor:
Maying Shen, Hongxu Yin, Jose M. Alvarez, Yerlan Idelbayev, Pavlo Molchanov, Miguel Á. Carreira-Perpiñán
Publikováno v:
CVPR
We study the problem of quantizing N sorted, scalar datapoints with a fixed codebook containing K entries that are allowed to be rescaled. The problem is defined as finding the optimal scaling factor α and the datapoint assignments into the α-scale
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c0fa068d7937e2fb930bfbed5d376462
https://doi.org/10.1109/cvpr46437.2021.01192
https://doi.org/10.1109/cvpr46437.2021.01192