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The Impact of Pan-Sharpening and Spectral Resolution on Vineyard Segmentation through Machine Learning.

, , , , , and . Remote. Sens., 12 (6): 934 (2020)

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Development productivity in implementing a complex heterogeneous computing application., , , and . FPT, page 322-325. IEEE, (2014)Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition., , , , , and . IEEE Trans. Image Processing, 26 (10): 4669-4683 (2017)The Impact of Pan-Sharpening and Spectral Resolution on Vineyard Segmentation through Machine Learning., , , , , and . Remote. Sens., 12 (6): 934 (2020)A data set for evaluating the performance of multi-class multi-object video tracking., , , , and . CoRR, (2017)The Visual Object Tracking VOT2013 Challenge Results., , , , , , , , , and 41 other author(s). ICCV Workshops, page 98-111. IEEE Computer Society, (2013)Chaining Convolution and Correlation in Practice: A Case Study in Visual Tracking., , , and . DICTA, page 1-8. IEEE, (2013)Automatic Ground Truths: Projected Image Annotations for Omnidirectional Vision., , , , , , , , and . DICTA, page 1-8. IEEE, (2017)Towards a Reconfigurable Tracking System., , and . FPL, page 456-462. IEEE, (2005)A Competitive Attentional Approach to Mitigating Model Drift in Adaptive Visual Tracking., , , , and . IVCNZ, page 1. ACM, (2014)The CACTuS multi-object visual tracking algorithm on a heterogeneous computing system., , , and . IVCNZ, page 19. ACM, (2014)