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On Scalable Data Mining Techniques for Earth Science.

, , , , , , and . ICCS, volume 51 of Procedia Computer Science, page 2188-2197. Elsevier, (2015)

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Automatic Framework for Spectral-Spatial Classification Based on Supervised Feature Extraction and Morphological Attribute Profiles., , , and . IEEE J Sel. Topics in Appl. Earth Observ. and Remote Sensing, 7 (6): 2147-2160 (2014)Remote Sensing Image Classification Using CNNs With Balanced Gradient for Distributed Heterogeneous Computing., , , , and . IEEE Geosci. Remote. Sens. Lett., (2022)Deep-Learning-Based 3-D Surface Reconstruction - A Survey., , , , , , and . Proc. IEEE, 111 (11): 1464-1501 (November 2023)A Single-Step Multiclass SVM Based on Quantum Annealing for Remote Sensing Data Classification., , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2024)Kernel Approximation on a Quantum Annealer for Remote Sensing Regression Tasks., , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2024)Local Binary and Multiclass SVMs Trained on a Quantum Annealer., , , , and . CoRR, (2024)Approaching Remote Sensing Image Classification with Ensembles of Support Vector Machines on the D-Wave Quantum Annealer., , , , and . IGARSS, page 1973-1976. IEEE, (2020)Super-Resolution of Large Volumes of Sentinel-2 Images with High Performance Distributed Deep Learning., , and . IGARSS, page 617-620. IEEE, (2020)Adiabatic Quantum Kitchen Sinks with Parallel Annealing for Remote Sensing Regression Problems., , , and . IGARSS, page 784-787. IEEE, (2023)On Understanding Big Data Impacts in Remotely Sensed Image Classification Using Support Vector Machine Methods., , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 8 (10): 4634-4646 (2015)