Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Andrew Achkar"'
Autor:
Ruixing Liang, Isaiah Djianto, J. Menard, Andrea Damascelli, Riccardo Comin, Christopher McMahon, Ronny Sutarto, W. N. Hardy, Andrew Achkar, E. H. da Silva Neto, D. A. Bonn, David Hawthorn, Feizhou He
Publikováno v:
Science Advances. 6
Charge density wave (CDW) order has been shown to compete and coexist with superconductivity in underdoped cuprates. Theoretical proposals for the CDW order include an unconventional $d$-symmetry form factor CDW, evidence for which has emerged from m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b15dd865c0cc05bfb1d6eb1cafc87cc8
https://doi.org/10.1126/sciadv.aay0345
https://doi.org/10.1126/sciadv.aay0345
Autor:
Shaozi Li, Zhiming Luo, Frederic B-Charron, Akshaya Mishra, Andrew Achkar, Janusz Konrad, Carl Lemaire, Pierre-Marc Jodoin, Justin A. Eichel
Publikováno v:
IEEE Transactions on Image Processing. 27:5129-5141
The ability to train on a large dataset of labeled samples is critical to the success of deep learning in many domains. In this paper, we focus on motor vehicle classification and localization from a single video frame and introduce the "MIOvision Tr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::55704b7f2f933aa5fb591335f6f22c66
https://doi.org/10.1109/tip.2018.2848705
https://doi.org/10.1109/tip.2018.2848705
Publikováno v:
CVPR
In this paper, we propose a new measure to gauge the complexity of image classification problems. Given an annotated image dataset, our method computes a complexity measure called the cumulative spectral gradient (CSG) which strongly correlates with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8fe7590ef7c35057d3627f647252c632
https://doi.org/10.1109/cvpr.2019.00333
https://doi.org/10.1109/cvpr.2019.00333
Publikováno v:
CVPR
Pruning methods have shown to be effective at reducing the size of deep neural networks while keeping accuracy almost intact. Among the most effective methods are those that prune a network while training it with a sparsity prior loss and learnable d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91b60fccbc73e57d0f03b814e685f028
https://doi.org/10.1109/cvpr.2019.00932
https://doi.org/10.1109/cvpr.2019.00932
Autor:
Riccardo Comin, L. Chauviere, Andrew Achkar, E. H. da Silva Neto, Bernhard Keimer, George A. Sawatzky, Yoshiyuki Yoshida, Feizhou He, D. A. Bonn, Walter Hardy, Andrea Damascelli, Ronny Sutarto, H. Eisaki, David Hawthorn, Alex Frano, Ruixing Liang
Publikováno v:
Nature Materials. 14:796-800
Charge-ordered ground states permeate the phenomenology of 3d-based transition metal oxides, and more generally represent a distinctive hallmark of strongly-correlated states of matter. The recent discovery of charge order in various cuprate families
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68f9d5da7efcca01df438c497442b604
https://doi.org/10.1038/nmat4295
https://doi.org/10.1038/nmat4295
Publikováno v:
CVPR
Saliency detection aims to highlight the most relevant objects in an image. Methods using conventional models struggle whenever salient objects are pictured on top of a cluttered background while deep neural nets suffer from excess complexity and slo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::333febefcfa2e8223473f98d32a4880d
https://doi.org/10.1109/cvpr.2017.698
https://doi.org/10.1109/cvpr.2017.698
Publikováno v:
CCECE
Sparsity in the weights of deep convolutional networks presents a tremendous opportunity to reduce computational requirements. In order to optimize flow of traffic systems, any viable solution must be able to operate at real-time. Existing computatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d3134813a7768ff4f7db424b4e374dbb
https://doi.org/10.1109/ccece.2017.7946788
https://doi.org/10.1109/ccece.2017.7946788
Publikováno v:
Journal of Computational Vision and Imaging Systems. 2
Human validation of computer vision systems increase their operatingcosts and limits their scale. Automated failure detection canmitigate these constraints and is thus of great importance to thecomputer vision industry. Here, we apply a deep neural n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1ad5210fbfe7675eda0982263adf839f
https://doi.org/10.15353/vsnl.v2i1.84
https://doi.org/10.15353/vsnl.v2i1.84
Autor:
Zhihao Hao, Christopher McMahon, H. Zhang, Feizhou He, Jochen Geck, A. Revcolevschi, Andrew Achkar, Isaiah Djianto, M. Zwiebler, Ronny Sutarto, Markus Hucker, Young-June Kim, Michel J. P. Gingras, David Hawthorn, G. D. Gu
In underdoped cuprate superconductors, a rich competition occurs between superconductivity and charge density wave (CDW) order. Whether rotational symmetry breaking (nematicity) occurs intrinsically and generically or as a consequence of other orders
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::77ed17dad96d6fe4abc34d43973c54c9
Autor:
Ruixing Liang, D. A. Bonn, Christopher McMahon, W. N. Hardy, Markus Hucker, M. Zwiebler, David Hawthorn, Genda Gu, Andrew Achkar, Ronny Sutarto, Feizhou He, Jochen Geck
Recent theories of charge density wave (CDW) order in high temperature superconductors have predicted a primarily d CDW orbital symmetry. Here, we report on the orbital symmetry of CDW order in the canonical cuprate superconductors La1.875Ba0.125CuO4
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fdcfaa5cb06a5eefb195b4ccdb68473c
http://arxiv.org/abs/1409.6787
http://arxiv.org/abs/1409.6787