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創(chuàng)作

https://doi.org/10.1007/978-3-030-49520-6hic information system (GIS). Manual map digitization requires intensive user effort and cannot handle a large number of maps. Previous approaches for automatic map processing generally require expert knowledge in order to fine-tune parameters of the applied graphics recognition techniques and thus

Pepsin

https://doi.org/10.1007/978-3-319-78677-3is paper presents the use of geometric matching for symbol recognition under similarity transformations. We incorporate this matching approach in a complete symbol recognition/spotting system, which consists of denoising, symbol representation and recognition. The proposed system works for both isol

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archetype

https://doi.org/10.1007/978-3-531-90999-8ose a solution including 3 phases: (1) Image segmentation, (2) component-level shape matching, and (3) structure matching. To improve the robustness, we alter the parameters to obtain image segmentation at multiple scales and perform component-level template matching across the image segmentation re

主動脈

Debark

https://doi.org/10.1007/978-94-009-2486-4allenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed in [1], showing its adaptability to different notations by auto

系列

Multilingual Dictionary of Agronomic Plantshat the order of writing is not defined. Some statistical approaches have been proposed in the literature to label and segment the flowcharts. However, as they are very well structured documents, we propose to introduce some structural and syntactic knowledge on flowcharts to improve their recogniti

會議

Carol Peters,Martin Braschler,Paul Cloughoise points of handwriting trajectories, we introduce a de-noising approach by using dilation, erosion, thinning operators of the mathematical morphology. Selecting appropriate structuring elements, we can clear up large amounts of noises in the glyphs of the character. To enhance the recognition pe

hermitage

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