DEEP NEURAL NETWORK ARCHITECTURE FOR SEMANTIC SEGMENTATION OF FORM IMAGES

摘要

#$%^&*AU2018203368A120190228.pdf#####DEEP NEURAL NETWORK ARCHITECTURE FOR SEMANTIC SEGMENTATION OF FORM IMAGES ABSTRACT OF THE DISCLOSURE A method and system for detecting and extracting accurate and precise structure in documents. A high-resolution image of documents is segmented into a set of tiles. Each tile is processed by a convolutional network and subsequently by a set of recurrent networks for each row and column. A global-lookup process is disclosed that allows "future" information required for accurate assessment by the recurrent neural networks to be considered. Utilization of high-resolution image allows for precise and accurate feature extraction while segmentation into tiles facilitates the tractable processing of the high-resolution image within reasonable computational resource bounds.1/14 1z 0UE D CL IV)V 0 * 0 E' CC~ 2 mw a U) 0=