Karthik Ganesan Pillai
Karthik Ganesan Pillai
Department of Computer Science, Montana State University
Verified email at cs.montana.edu - Homepage
Cited by
Cited by
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
A Filter-and-Refine Approach to Mine Spatiotemporal Co-occurrences
KG Pillai, RA Angryk, B Aydin
Proceedings of the 21th International Conference on Advances in Geographic …, 2013
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
Spatiotemporal indexing techniques for efficiently mining spatiotemporal co-occurrence patterns
B Aydin, D Kempton, V Akkineni, SR Gopavaram, KG Pillai, R Angryk
2014 IEEE international conference on big data (Big Data), 1-10, 2014
DOSI: Training Artificial Neural Networks using Overlapping Swarm Intelligence with Local Credit Assignment''
KGP Nathan Fortier, John Sheppard
SCIS-ISIS, 1420-1425, 2012
Iterative refinement of multiple targets tracking of solar events
D Kempton, KG Pillai, R Angryk
2014 IEEE International Conference on Big Data (Big Data), 36-44, 2014
Overlapping swarm intelligence for training artificial neural networks
KG Pillai, JW Sheppard
2011 IEEE Symposium on Swarm Intelligence, 1-8, 2011
Spatiotemporal co-occurrence rules
KG Pillai, RA Angryk, JM Banda, T Wylie, MA Schuh
New Trends in Databases and Information Systems, 27-35, 2014
ERMO-DG: Evolving Region Moving Object Dataset Generator
B Aydin, RA Angryk, KG Pillai
Proc. of the 27th International Florida Artificial Intelligence Research …, 2014
Bayesian abductive inference using overlapping swarm intelligence
N Fortier, J Sheppard, KG Pillai
2013 IEEE Symposium on Swarm Intelligence (SIS), 263-270, 2013
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
Mining spatiotemporal co-occurrence patterns in solar datasets
B Aydin, D Kempton, V Akkineni, R Angryk, KG Pillai
Astronomy and computing 13, 136-144, 2015
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
Mining at most top-k% spatiotemporal co-occurrence patterns in datasets with extended spatial representations
KG Pillai, RA Angryk, JM Banda, D Kempton, B Aydin, PC Martens
ACM Transactions on Spatial Algorithms and Systems (TSAS) 2 (3), 1-27, 2016
Multi-sensor Remote Sensing Image Change Detection: An Evaluation of Similarity Measures
KG Pillai, RR Vatsavai
ICDM Workshops 2013, 2013
Abductive Inference in Bayesian Belief Networks Using Swarm Intelligence
JS Karthik Ganesan Pillai
SCIS-ISIS, 375-380, 2012
Parallel simulated annealing for VLSI cell placement problem
A Roy, KG Pillai
Montana State University, 2009
Extending High-Dimensional Indexing Techniques Pyramid and iMinMax(θ): Lessons Learned
KG Pillai, L Sturlaugson, JM Banda, RA Angryk
British National Conference on Databases, 253-267, 2013
Hemispheric Patterns in Filament Chirality and Sigmoid Shape over the Solar Cycle
PC Martens, AR Yeates, KG Pillai
Mining spatiotemporal co-occurrence patterns from massive data sets with evolving regions
KG Pillai
Montana State University, 2014
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