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Quantitative Comparison of Linear and Non-linear Dimensionality Reduction Techniques for Solar Image Archives.

, , and . FLAIRS, AAAI Press, (2012)

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A filter-and-refine approach to mine spatiotemporal co-occurrences., , and . SIGSPATIAL/GIS, page 104-113. ACM, (2013)Automated Generalization of Fuzzy Concept Hierarchies for Attribute-Oriented Induction Purposes., and . Databases and Applications, page 66-74. IASTED/ACTA Press, (2006)Special issue on deep learning for time series data., , and . Neural Comput. Appl., 34 (16): 13147-13148 (2022)MVTS-Data Toolkit: A Python package for preprocessing multivariate time series data., , , and . SoftwareX, (2020)Solar image parameter data from the SDO: Long-term curation and data mining., , and . Astron. Comput., (2015)Spatiotemporal Co-occurrence Rules., , , , and . ADBIS (2), volume 241 of Advances in Intelligent Systems and Computing, page 27-35. Springer, (2013)On Interpretation of Non-atomic Values and Induction of Decision Rules in Fuzzy Relational Databases.. ICAISC, volume 4029 of Lecture Notes in Computer Science, page 170-181. Springer, (2006)Understanding the Impact of Statistical Time Series Features for Flare Prediction Analysis., , , , , and . IEEE BigData, page 4960-4966. IEEE, (2019)Deep Neural Network-based Active Region Magnetogram Patch Super Resolution., , , , and . IEEE BigData, page 4200-4207. IEEE, (2020)Massive labeled solar image data benchmarks for automated feature recognition., and . IEEE BigData, page 53-60. IEEE Computer Society, (2014)