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Explosive hazard detection with feature and decision level fusion, multiple kernel learning, and fuzzy integrals.

, , , , , and . SSCI, page 1-8. IEEE, (2016)

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Constraints Preserving Genetic Algorithm for Learning Fuzzy Measures with an Application to Ontology Matching., , and . WCSC, volume 312 of Studies in Fuzziness and Soft Computing, page 93-103. Springer, (2013)Causal cueing system for above ground anomaly detection of explosive hazards using support vector machine localized by K-nearest neighbor., , , and . CISDA, page 1-8. IEEE, (2012)Hybrid Measure of Agreement and Expertise for Ontology Matching in Lieu of a Reference Ontology., , and . Int. J. Intell. Syst., 31 (5): 502-525 (2016)Multi-criteria based learning of the Choquet integral using Goal programming., , and . NAFIPS/WConSC, page 1-6. IEEE, (2015)Aggregating Deep Convolutional Neural Network Scans of Broad-Area High-Resolution Remote Sensing Imagery., , , , and . IGARSS, page 665-668. IEEE, (2018)Comparing Fuzzy, Probabilistic, and Possibilistic Partitions Using the Earth Mover's Distance., , and . IEEE Trans. Fuzzy Syst., 21 (4): 766-775 (2013)Introducing Fuzzy Layers for Deep Learning., , and . CoRR, (2020)Enhanced Fusion of Deep Neural Networks for Classification of Benchmark High-Resolution Image Data Sets., , , , , and . IEEE Geosci. Remote. Sens. Lett., 15 (9): 1451-1455 (2018)Fusion of heterogeneous bands and kernels in hyperspectral image processing., , , and . CoRR, (2019)Machine Learning of Choquet Integral Regression with Respect to a Bounded Capacity (or Non-monotonic Fuzzy Measure)., and . FUZZ-IEEE, page 1-6. IEEE, (2019)