Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Vardan Papyan"'
Autor:
Dhiraj J. Pangal, Guillaume Kugener, Yichao Zhu, Aditya Sinha, Vyom Unadkat, David J. Cote, Ben Strickland, Martin Rutkowski, Andrew Hung, Animashree Anandkumar, X. Y. Han, Vardan Papyan, Bozena Wrobel, Gabriel Zada, Daniel A. Donoho
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)
Abstract Major vascular injury resulting in uncontrolled bleeding is a catastrophic and often fatal complication of minimally invasive surgery. At the outset of these events, surgeons do not know how much blood will be lost or whether they will succe
Externí odkaz:
https://doaj.org/article/c964f61c59dd458fa1fe9545d78e34ea
Publikováno v:
Art Documentation: Journal of the Art Libraries Society of North America. 40:1-20
The Frick Art Reference Library in New York launched a pilot project with Stanford University, Cornell University, and the University of Toronto to develop an algorithm that applies a local...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77b42291b66fcc7080ec8eef0383f73e
https://doi.org/10.1086/714604
https://doi.org/10.1086/714604
Autor:
Guillaume, Kugener, Dhiraj J, Pangal, Tyler, Cardinal, Casey, Collet, Elizabeth, Lechtholz-Zey, Sasha, Lasky, Shivani, Sundaram, Nicholas, Markarian, Yichao, Zhu, Arman, Roshannai, Aditya, Sinha, X Y, Han, Vardan, Papyan, Andrew, Hung, Animashree, Anandkumar, Bozena, Wrobel, Gabriel, Zada, Daniel A, Donoho
Importance. Surgical data scientists lack video data sets that depict adverse events, which may affect model generalizability and introduce bias. Hemorrhage may be particularly challenging for computer vision–based models because blood obscures the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad4f1b78eabb51d895c7c44f8a85e9d6
https://resolver.caltech.edu/CaltechAUTHORS:20220329-772928599
https://resolver.caltech.edu/CaltechAUTHORS:20220329-772928599
Autor:
Dhiraj J. Pangal, Guillaume Kugener, Yichao Zhu, Aditya Sinha, Vyom Unadkat, David J. Cote, Arman Roshannai, Ben Strickland, Martin Rutkowski, Andrew Hung, Animashree Anandkumar, X. Y. Han, Vardan Papyan, Bozena Wrobel, Gabriel Zada, Daniel A. Donoho
Publikováno v:
31st Annual Meeting North American Skull Base Society.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::87dc029bf1e0f75f736d58020acf4230
https://doi.org/10.1055/s-0042-1743643
https://doi.org/10.1055/s-0042-1743643
Autor:
Dhiraj J. Pangal, Guillaume Kugener, Yichao Zhu, Aditya Sinha, Vyom Unadkat, David J. Cote, Ben Strickland, Martin Rutkowski, Andrew Hung, Animashree Anandkumar, X. Y. Han, Vardan Papyan, Bozena Wrobel, Gabriel Zada, Daniel A. Donoho
Publikováno v:
Scientific reports. 12(1)
Major vascular injury resulting in uncontrolled bleeding is a catastrophic and often fatal complication of minimally invasive surgery. At the outset of these events, surgeons do not know how much blood will be lost or whether they will successfully c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7291d0f0ed93f159427a3dcaa55ff383
https://pubmed.ncbi.nlm.nih.gov/35581213
https://pubmed.ncbi.nlm.nih.gov/35581213
Modern practice for training classification deepnets involves a terminal phase of training (TPT), which begins at the epoch where training error first vanishes. During TPT, the training error stays effectively zero, while training loss is pushed towa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd416d43557f35af2696dec5312060f1
Publikováno v:
IEEE Signal Processing Magazine. 35:72-89
Modeling data is the way we-scientists-believe that information should be explained and handled. Indeed, models play a central role in practically every task in signal and image processing and machine learning. Sparse representation theory (we shall
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0051ff5bf8f49576cca5b5cffa88e80a
https://doi.org/10.1109/msp.2018.2820224
https://doi.org/10.1109/msp.2018.2820224
Autor:
Vardan Papyan, Ronen Talmon
Publikováno v:
Signal Processing. 142:178-187
Consider a set of multiple, multimodal sensors capturing a complex system or a physical phenomenon of interest. Our primary goal is to distinguish the underlying sources of variability manifested in the measured data. The first step in our analysis i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5629f5ad5d16d912c652d21d300018ef
https://doi.org/10.1016/j.sigpro.2017.07.016
https://doi.org/10.1016/j.sigpro.2017.07.016
Publikováno v:
IEEE Transactions on Signal Processing. 65:5687-5701
The celebrated sparse representation model has led to remarkable results in various signal processing tasks in the last decade. However, despite its initial purpose of serving as a global prior for entire signals, it has been commonly used for modeli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e21b4b297fe2931f6b5884a668315413
https://doi.org/10.1109/tsp.2017.2733447
https://doi.org/10.1109/tsp.2017.2733447