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ORCIDSamuel J. Yang
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Journal Articles
- 2018
[j2]Samuel J. Yang
, Marc Berndl, D. Michael Ando, Mariya Barch, Arunachalam Narayanaswamy, Eric Christiansen, Stephan Hoyer, Chris Roat, Jane Hung, Curtis T. Rueden, Asim Shankar, Steven Finkbeiner, Philip Nelson:
Assessing microscope image focus quality with deep learning. BMC Bioinform. 19(1): 77:1-77:9 (2018)- 2015
- [j1]Isaac Kauvar, Samuel J. Yang, Liang Shi, Ian McDowall, Gordon Wetzstein:
Adaptive color display via perceptually-driven factored spectral projection. ACM Trans. Graph. 34(6): 165:1-165:10 (2015)
Conference and Workshop Papers
- 2023
- [c4]Subhashini Venugopalan, Jimmy Tobin, Samuel J. Yang, Katie Seaver, Richard J. N. Cave, Pan-Pan Jiang, Neil Zeghidour, Rus Heywood, Jordan R. Green, Michael P. Brenner:
Speech Intelligibility Classifiers from 550k Disordered Speech Samples. ICASSP 2023: 1-5 - [c3]Artem Dementyev, Dimitri Kanevsky, Samuel J. Yang, Mathieu Parvaix, Chiong Lai, Alex Olwal:
LiveLocalizer: Augmenting Mobile Speech-to-Text with Microphone Arrays, Optimized Localization and Beamforming. UIST (Adjunct Volume) 2023: 75:1-75:3 - 2022
- [c2]Samuel J. Yang, Scott Wisdom, Chet Gnegy, Richard F. Lyon, Sagar Savla:
Listening with Googlears: Low-Latency Neural Multiframe Beamforming and Equalization for Hearing Aids. INTERSPEECH 2022: 3939-3943 - 2021
- [c1]Colin L. V. Cooke, Fanjie Kong, Amey Chaware, Kevin C. Zhou, Kanghyun Kim, Rong Xu, D. Michael Ando, Samuel J. Yang, Pavan Chandra Konda, Roarke Horstmeyer:
Physics-Enhanced Machine Learning for Virtual Fluorescence Microscopy. ICCV 2021: 3783-3793
Informal and Other Publications
- 2023
- [i3]Subhashini Venugopalan, Jimmy Tobin, Samuel J. Yang, Katie Seaver, Richard J. N. Cave, Pan-Pan Jiang, Neil Zeghidour, Rus Heywood, Jordan R. Green, Michael P. Brenner:
Speech Intelligibility Classifiers from 550k Disordered Speech Samples. CoRR abs/2303.07533 (2023) - 2020
- [i2]Colin L. V. Cooke, Fanjie Kong, Amey Chaware, Kevin C. Zhou, Kanghyun Kim, Rong Xu, D. Michael Ando, Samuel J. Yang, Pavan Chandra Konda, Roarke Horstmeyer:
Physics-enhanced machine learning for virtual fluorescence microscopy. CoRR abs/2004.04306 (2020) - 2019
- [i1]Subhashini Venugopalan, Arunachalam Narayanaswamy, Samuel J. Yang, Anton Gerashcenko, Scott Lipnick, Nina Makhortova, James Hawrot, Christine Marques, Joao Pereira, Michael P. Brenner, Lee Rubin, Brian Wainger, Marc Berndl:
It's easy to fool yourself: Case studies on identifying bias and confounding in bio-medical datasets. CoRR abs/1912.07661 (2019)
Coauthor Index
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