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A Possible Reason for why Data-Driven Beats Theory-Driven Computer Vision., , , and . CoRR, (2019)A Low Power, Fully Event-Based Gesture Recognition System., , , , , , , , , and 6 other author(s). CVPR, page 7388-7397. IEEE Computer Society, (2017)A low-power neurosynaptic implementation of Local Binary Patterns for texture analysis., , , and . IJCNN, page 4308-4316. IEEE, (2016)Why Does Data-Driven Beat Theory-Driven Computer Vision?, , , and . ICCV Workshops, page 2057-2060. IEEE, (2019)A Novel Algorithm for Fitting 3-D Active Appearance Models: Applications to Cardiac MRI Segmentation., and . SCIA, volume 3540 of Lecture Notes in Computer Science, page 729-739. Springer, (2005)TrueNorth: Accelerating From Zero to 64 Million Neurons in 10 Years., , , , , , , , , and 18 other author(s). Computer, 52 (5): 20-29 (2019)Resampling 4-D Images Using Adaptive Filtering., and . CRV, page 18-26. IEEE Computer Society, (2005)LATTE: Low-power Audio Transform with TrueNorth Ecosystem., , , , , , , , , and . IJCNN, page 4270-4277. IEEE, (2016)50 Years of object recognition: Directions forward., and . Comput. Vis. Image Underst., 117 (8): 827-891 (2013)Efficient and generalizable statistical models of shape and appearance for analysis of cardiac MRI., and . Medical Image Anal., 12 (3): 335-357 (2008)