Zobrazeno 1 - 10
of 152
pro vyhledávání: '"Ramakrishnan, Anand"'
Autor:
Vidler, Callum, Halwes, Michael, Kolesnik, Kirill, Segeritz, Philipp, Mail, Matthew, Barlow, Anders J., Koehl, Emmanuelle M., Ramakrishnan, Anand, Scott, Daniel J., Heath, Daniel E., Crozier, Kenneth B., Collins, David J.
Additive manufacturing is an expanding multidisciplinary field encompassing applications including medical devices, aerospace components, microfabrication strategies, and artificial organs. Among additive manufacturing approaches, light-based printin
Externí odkaz:
http://arxiv.org/abs/2403.15144
Autor:
Gearing, Peter F., El-Atem, Nathan, Devine, Maxim, Chen, Jane, Kumar, Ricky, Ramakrishnan, Anand, Nastri, Alf
Publikováno v:
In Journal of Cranio-Maxillo-Facial Surgery October 2024 52(10):1088-1094
Autor:
Ramakrishnan, Anand1, Popat, Dillon2, Purushothaman, Preetha1, Chan, Li F.1,2, Gevers, Evelien F.1,2 Evelien.gevers@nhs.net
Publikováno v:
JCEM Case Reports. Aug2024, Vol. 2 Issue 8, p1-7. 7p.
Publikováno v:
In Journal of Plastic, Reconstructive & Aesthetic Surgery June 2024 93:18-23
For the task of face verification, we explore the utility of harnessing auxiliary facial emotion labels to impose explicit geometric constraints on the embedding space when training deep embedding models. We introduce several novel loss functions tha
Externí odkaz:
http://arxiv.org/abs/2103.03862
Deep learning models are trained to minimize the error between the model's output and the actual values. The typical cost function, the Mean Squared Error (MSE), arises from maximizing the log-likelihood of additive independent, identically distribut
Externí odkaz:
http://arxiv.org/abs/2008.03582
Autor:
Ramakrishnan, Anand, Zylich, Brian, Ottmar, Erin, LoCasale-Crouch, Jennifer, Whitehill, Jacob
Publikováno v:
IEEE Transactions on Affective Computing, 2021
In this work we present a multi-modal machine learning-based system, which we call ACORN, to analyze videos of school classrooms for the Positive Climate (PC) and Negative Climate (NC) dimensions of the CLASS observation protocol that is widely used
Externí odkaz:
http://arxiv.org/abs/2005.09525
Akademický článek
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Autor:
Whitehill, Jacob, Ramakrishnan, Anand
Automatic machine learning-based detectors of various psychological and social phenomena (e.g., emotion, stress, engagement) have great potential to advance basic science. However, when a detector $d$ is trained to approximate an existing measurement
Externí odkaz:
http://arxiv.org/abs/1812.08255
Akademický článek
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