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Learning Spatial Relationships between Samples of Patent Image Shapes
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Binary image based classification and retrieval of documents of an intellectual nature is a very challenging problem. Variations in the binary image generation mechanisms which are subject to the document artisan designer including drawing style, view-point, inclusion of multiple image components are plausible causes for increasing the complexity of the problem. In this work, we propose a method suitable to binary images which bridges some of the successes of deep learning (DL) to alleviate thedoi:10.1109/cvprw50498.2020.00094 dblp:conf/cvpr/CastorenaBO20 fatcat:brfu5awny5h4xdn3sdalk3rumq