Michael A. Schuh
Michael A. Schuh
Dept of Computer Science, Montana State University
Verified email at cs.montana.edu - Homepage
Title
Cited by
Cited by
Year
A large-scale solar image dataset with labeled event regions
MA Schuh, RA Angryk, KG Pillai, JM Banda, PC Martens
2013 IEEE International Conference on Image Processing, 4349-4353, 2013
502013
Spatio-temporal co-occurrence pattern mining in data sets with evolving regions
KG Pillai, RA Angryk, JM Banda, MA Schuh, T Wylie
2012 IEEE 12th International Conference on Data Mining Workshops, 805-812, 2012
372012
A comparative evaluation of automated solar filament detection
MA Schuh, JM Banda, PN Bernasconi, RA Angryk, PCH Martens
Solar Physics 289 (7), 2503-2524, 2014
212014
Graph-based ontology-guided data mining for D-matrix model maturation
S Strasser, J Sheppard, M Schuh, R Angryk, C Izurieta
2011 Aerospace Conference, 1-12, 2011
212011
Spatiotemporal co-occurrence rules
KG Pillai, RA Angryk, JM Banda, T Wylie, MA Schuh
New Trends in Databases and Information Systems, 27-35, 2014
192014
Multivariate time series dataset for space weather data analytics
RA Angryk, PC Martens, B Aydin, D Kempton, SS Mahajan, S Basodi, ...
Scientific data 7 (1), 1-13, 2020
162020
A comprehensive study of idistance partitioning strategies for knn queries and high-dimensional data indexing
MA Schuh, T Wylie, JM Banda, RA Angryk
British National Conference on Databases, 238-252, 2013
162013
On visualization techniques for solar data mining
MA Schuh, JM Banda, T Wylie, P McInerney, KG Pillai, RA Angryk
Astronomy and computing 10, 32-42, 2015
152015
When too similar is bad: A practical example of the solar dynamics observatory content-based image-retrieval system
JM Banda, MA Schuh, T Wylie, P McInerney, RA Angryk
New Trends in Databases and Information Systems, 87-95, 2014
152014
SPRINTS: A framework for solar‐driven event forecasting and research
AJ Engell, DA Falconer, M Schuh, J Loomis, D Bissett
Space Weather 15 (10), 1321-1346, 2017
142017
Massive labeled solar image data benchmarks for automated feature recognition
MA Schuh, RA Angryk
2014 IEEE International Conference on Big Data (Big Data), 53-60, 2014
142014
An IEEE standards-based visualization tool for knowledge discovery in maintenance event sequences
M Schuh, J Sheppard, S Strasser, R Angryk, C Izurieta
IEEE Aerospace and Electronic Systems Magazine 28 (7), 30-39, 2013
122013
Ontology-guided knowledge discovery of event sequences in maintenance data
M Schuh, J Sheppard, S Strasser, R Angryk, C Izurieta
2011 IEEE AUTOTESTCON, 279-285, 2011
122011
Big data new frontiers: mining, search and management of massive repositories of solar image data and solar events
JM Banda, MA Schuh, RA Angryk, KG Pillai, P McInerney
New Trends in Databases and Information Systems, 151-158, 2014
112014
A large-scale dataset of solar event reports from automated feature recognition modules
MA Schuh, RA Angryk, PC Martens
Journal of Space Weather and Space Climate 6, A22, 2016
102016
Mitigating the curse of dimensionality for exact knn retrieval
MA Schuh, T Wylie, RA Angryk
The Twenty-Seventh International Flairs Conference, 2014
102014
Evolving kernel functions with particle swarms and genetic programming
MA Schuh, R Angryk, J Sheppard
Twenty-Fifth International FLAIRS Conference, 2012
102012
Spatiotemporal interpolation methods for solar event trajectories
SF Boubrahimi, B Aydin, MA Schuh, D Kempton, RA Angryk, R Ma
The Astrophysical Journal Supplement Series 236 (1), 23, 2018
92018
Solar image parameter data from the sdo: Long-term curation and data mining
MA Schuh, RA Angryk, PC Martens
Astronomy and computing 13, 86-98, 2015
92015
Improving the performance of high-dimensional knn retrieval through localized dataspace segmentation and hybrid indexing
MA Schuh, T Wylie, RA Angryk
East European Conference on Advances in Databases and Information Systems …, 2013
92013
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Articles 1–20