Document image classification is the task of classifying documents based on images of their contents.
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In this paper, we propose the LayoutLM to jointly model the interaction between text and layout information across scanned document images, which is beneficial for a great number of real-world document image understanding tasks such as information extraction from scanned documents.
In this work, a region-based Deep Convolutional Neural Network framework is proposed for document structure learning.
#2 best model for Document Image Classification on RVL-CDIP
We present an exhaustive investigation of recent Deep Learning architectures, algorithms, and strategies for the task of document image classification to finally reduce the error by more than half.
#3 best model for Document Image Classification on RVL-CDIP