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Deep Learning Hyperspectral Image Classification using Multiple Class-Based Denoising Autoencoders, Mixed Pixel Training Augmentation, and Morphological Operations., и . IGARSS, стр. 6903-6906. IEEE, (2018)CLODD based band group selection., , , и . IGARSS, стр. 36-39. IEEE, (2016)A Comprehensive Survey of Deep Learning in Remote Sensing: Theories, Tools and Challenges for the Community., , и . CoRR, (2017)Fusion of diverse features and kernels using LP-norm based multiple kernel learning in hyperspectral image processing., , , и . WHISPERS, стр. 1-5. IEEE, (2016)Engaging Students in an Automotive Autonomy Sensor Processing Class: Incorporating active learning and high-fidelity, physics-based autonomy simulation into class projects., , и . IEEE Signal Process. Mag., 38 (3): 122-132 (2021)Closing the Wearable Gap - Part V: Development of a Pressure-Sensitive Sock Utilizing Soft Sensors., , , , , , , , и . Sensors, 20 (1): 208 (2020)Closing the Wearable Gap - Part II: Sensor Orientation and Placement for Foot and Ankle Joint Kinematic Measurements., , , , , , , , , и 1 other автор(ы). Sensors, 19 (16): 3509 (2019)Fusion of heterogeneous bands and kernels in hyperspectral image processing., , , и . CoRR, (2019)Onion-Peeling Outlier Detection in 2-D data Sets., , и . CoRR, (2018)CaT: CAVS Traversability Dataset for Off-Road Autonomous Driving., , , , , , , , , и 1 other автор(ы). IEEE Access, (2022)