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Comparing inference methods for conditional random fields for hyperspectral image classification.

, , and . WHISPERS, page 1-4. IEEE, (2015)

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Consistency of Measurements of Wavelength Position From Hyperspectral Imagery: Use of the Ferric Iron Crystal Field Absorption at ~900 nm as an Indicator of Mineralogy., , and . IEEE Trans. Geosci. Remote. Sens., 52 (5): 2843-2857 (2014)Spectral angle based unary energy functions for spatial-spectral hyperspectral classification using Markov random fields., and . WHISPERS, page 1-6. IEEE, (2016)Feature selection with PSO and kernel methods for hyperspectral classification., and . IEEE Congress on Evolutionary Computation, page 1762-1769. IEEE, (2011)Vehicle detection from aerial color imagery and airborne LiDAR data., , and . IGARSS, page 1384-1387. IEEE, (2016)Editorial: Special issue on Alternative Sensing Techniques for Robot Perception., , , and . J. Field Robotics, 32 (1): 1-2 (2015)Evaluating techniques for learning a feedback controller for low-cost manipulators., and . IROS, page 704-709. IEEE, (2013)Classification of hyperspectral images based on conditional random fields., , , , and . Image Processing: Machine Vision Applications, volume 9405 of SPIE Proceedings, page 940510. SPIE, (2015)Gaussian Processes for Object Detection in High Resolution Remote Sensing Images., , and . ICMLA, page 998-1003. IEEE Computer Society, (2016)A Tutorial on Modeling and Inference in Undirected Graphical Models for Hyperspectral Image Analysis., and . CoRR, (2018)Comparing inference methods for conditional random fields for hyperspectral image classification., , and . WHISPERS, page 1-4. IEEE, (2015)