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ORCIDMichael J. Turmon
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2020 – today
- 2023
[i4]Anshuman Pradhan, Kyra H. Adams, Venkat Chandrasekaran, Zhen Liu, John T. Reager, Andrew M. Stuart, Michael J. Turmon:
Modeling groundwater levels in California's Central Valley by hierarchical Gaussian process and neural network regression. CoRR abs/2310.14555 (2023)- 2022
- [i3]Kyongsik Yun, Kyra Adams, John T. Reager, Zhen Liu, Caitlyn Chavez, Michael J. Turmon, Thomas Lu:
Remote estimation of geologic composition using interferometric synthetic-aperture radar in California's Central Valley. CoRR abs/2212.04813 (2022)
2010 – 2019
- 2016
- [j5]S. George Djorgovski, Matthew J. Graham, Ciro Donalek, Ashish Mahabal, Andrew J. Drake, Michael J. Turmon, Thomas J. Fuchs:
Real-time data mining of massive data streams from synoptic sky surveys. Future Gener. Comput. Syst. 59: 95-104 (2016) - [i2]S. George Djorgovski, Matthew J. Graham, Ciro Donalek, Ashish Mahabal, Andrew J. Drake, Michael J. Turmon, Thomas J. Fuchs:
Real-Time Data Mining of Massive Data Streams from Synoptic Sky Surveys. CoRR abs/1601.04385 (2016) - 2014
- [c10]S. George Djorgovski, Ashish Mahabal, Ciro Donalek, Matthew J. Graham, Andrew J. Drake, Michael J. Turmon, Thomas J. Fuchs:
Automated Real-Time Classification and Decision Making in Massive Data Streams from Synoptic Sky Surveys. eScience 2014: 204-211 - 2013
- [c9]Ciro Donalek, S. George Djorgovski, Ashish Mahabal, Matthew J. Graham, Andrew J. Drake, Arun Kumar A., N. Sajeeth Philip, Thomas J. Fuchs, Michael J. Turmon, Michael Ting-Chang Yang, Giuseppe Longo:
Feature selection strategies for classifying high dimensional astronomical data sets. IEEE BigData 2013: 35-41 - [i1]Ciro Donalek, Arun Kumar A., S. George Djorgovski, Ashish Mahabal, Matthew J. Graham, Thomas J. Fuchs, Michael J. Turmon, N. Sajeeth Philip, Michael Ting-Chang Yang, Giuseppe Longo:
Feature Selection Strategies for Classifying High Dimensional Astronomical Data Sets. CoRR abs/1310.1976 (2013) - 2012
- [c8]S. George Djorgovski, Ashish Mahabal, Ciro Donalek, Matthew J. Graham, Andrew J. Drake, Baback Moghaddam, Mike Turmon:
Flashes in a star stream: Automated classification of astronomical transient events. eScience 2012: 1-8 - 2011
- [c7]S. George Djorgovski, Ciro Donalek, Ashish Mahabal, Baback Moghaddam, Mike Turmon, Matthew J. Graham, Andrew J. Drake, Nihar Sharma, Yutong Chen:
Towards an Automated Classification of Transient Events in Synoptic Sky Surveys. CIDU 2011: 174-188
2000 – 2009
- 2009
- [j4]Max Bajracharya, Andrew Howard, Larry H. Matthies, Benyang Tang, Michael J. Turmon:
Autonomous off-road navigation with end-to-end learning for the LAGR program. J. Field Robotics 26(1): 3-25 (2009) - 2008
- [c6]Max Bajracharya, Benyang Tang, Andrew Howard, Michael J. Turmon, Larry H. Matthies:
Learning long-range terrain classification for autonomous navigation. ICRA 2008: 4018-4024 - 2006
- [j3]Andrew Howard, Michael J. Turmon, Larry H. Matthies, Benyang Tang, Anelia Angelova, Eric Mjolsness:
Towards learned traversability for robot navigation: From underfoot to the far field. J. Field Robotics 23(11-12): 1005-1017 (2006) - 2003
- [j2]Michael J. Turmon, Robert Granat, Daniel S. Katz
, John Z. Lou:
Tests and Tolerances for High-Performance Software-Implemented Fault Detection. IEEE Trans. Computers 52(5): 579-591 (2003) - 2000
- [c5]Michael J. Turmon, Robert Granat, Daniel S. Katz:
Software-Implemented Fault Detection for High-Performance Space Applications. DSN 2000: 107-116
1990 – 1999
- 1998
- [c4]Michael J. Turmon, Saleem Mukhtar:
Representing Solar Active Regions with Triangulations. COMPSTAT 1998: 473-478 - 1997
- [c3]Michael J. Turmon, Saleem Mukhtar:
Recognizing chromospheric objects via Markov chain Monte Carlo. ICIP (3) 1997: 320-323 - [c2]Michael J. Turmon, Saleem Mukhtar, Judit Pap:
Bayesian Inference for Identifying Solar Active Regions. KDD 1997: 267-270 - 1994
- [j1]Michael J. Turmon, Michael I. Miller:
Maximum-likelihood estimation of complex sinusoids and Toeplitz covariances. IEEE Trans. Signal Process. 42(5): 1074-1086 (1994) - [c1]Michael J. Turmon, Terrence Fine:
Sample Size Requirements for Feedforward Neural Networks. NIPS 1994: 327-334
Coauthor Index
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