Jul 22, 2016 · Abstract: This letter evaluates metaheuristics for the supervised parameter tuning of multiresolution-region-growing segmentation.
Abstract—This letter evaluates metaheuristics for the super- vised parameter tuning of multiresolution-region-growing seg- mentation.
Metaheuristics for Supervised Parameter Tuning of Multiresolution ...
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This letter evaluates metaheuristics for the supervised parameter tuning of multiresolution-region-growing segmentation. Three groups of metaheuristics are ...
This letter evaluates metaheuristics for the supervised parameter tuning of multiresolution-region-growing segmentation. Three groups of metaheuristics are ...
This letter evaluates metaheuristics for the supervised parameter tuning of multiresolution-region-growing segmentation. Three groups of metaheuristics are ...
Publication: Metaheuristics for Supervised Parameter Tuning of ...
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Metaheuristics for Supervised Parameter Tuning of Multiresolution Segmentation. Victor Andres Ayma Pedro Achanccaray Diaz Raul Queiroz Feitosa Patrick Nigri ...
The proposed framework couples different optimisation algorithms to solve single-objective optimisation problems. The supervision balances the exploration and ...
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Metaheuristics for Supervised Parameter Tuning of Multiresolution Segmentation · A Survey of Automatic Parameter Tuning Methods for Metaheuristics · Efficient GPU ...
Sep 5, 2018 · First, multiresolution segmentation was optimized through the synergy of the F1-score accuracy measure and the robust Taguchi design. Second, ...
Supervised methods are designed to measure the dissimilarity between segmentation results and user-generated (e.g., hand digitized) reference objects. The ...
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