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A Survey on Deep learning based Document Image Enhancement [article]

Zahra Anvari, Vassilis Athitsos
2022 arXiv   pre-print
Document image enhancement plays a crucial role as a pre-processing step in many automated document analysis and recognition tasks such as character recognition.  ...  Digitized documents such as scientific articles, tax forms, invoices, contract papers, historic texts are widely used nowadays.  ...  This network is based on conditional GANs, cGANs, network to restore severely degraded document images.  ... 
arXiv:2112.02719v4 fatcat:sznkn6vkr5fabag2pmaff6bhky

Deep Learning for Historical Document Analysis and Recognition—A Survey

Francesco Lombardi, Simone Marinai
2020 Journal of Imaging  
Nowadays, deep learning methods are employed in a broad range of research fields. The analysis and recognition of historical documents, as we survey in this work, is not an exception.  ...  Our study analyzes the papers published in the last few years on this topic from different perspectives: we first provide a pragmatic definition of historical documents from the point of view of the research  ...  [42] propose a character attention generative adversarial network named CAGAN for restoring heavily degraded character patterns in historical documents so that OCRs can improve their accuracy and help  ... 
doi:10.3390/jimaging6100110 pmid:34460551 pmcid:PMC8321201 fatcat:nevh2ctshzfwtey4girgjtaftq

Blur2Sharp: A GAN-Based Model for Document Image Deblurring

Hala Neji, Mohamed Ben Halima, Tarek M. Hamdani, Javier Nogueras-Iso, Adel M. Alimi
2021 International Journal of Computational Intelligence Systems  
This work proposes an end-to-end model for document deblurring using cycle-consistent adversarial networks.  ...  Our method, named "Blur2Sharp CycleGAN, " generates a sharp image from a blurry one and shows how cycle-consistent generative adversarial networks (CycleGAN) can be used in document deblurring.  ...  In addition, we gratefully acknowledge the support of NVIDIA Corporation with the donation of the Quadro P6000 GPU used for this research.  ... 
doi:10.2991/ijcis.d.210407.001 fatcat:7724ts57tvddbaycu5ydr33qqe

DE-GAN: A Conditional Generative Adversarial Network for Document Enhancement

Mohamed Ali Souibgui, Yousri Kessentini
2020 IEEE Transactions on Pattern Analysis and Machine Intelligence  
In this paper, we propose an effective end-to-end framework named Document Enhancement Generative Adversarial Networks (DE-GAN) that uses the conditional GANs (cGANs) to restore severely degraded document  ...  To the best of our knowledge, this practice has not been studied within the context of generative adversarial deep networks.  ...  CONCLUSION In this paper we proposed a Document Enhancement Generative Adversarial Network named DE-GAN to restore severely degraded document images.  ... 
doi:10.1109/tpami.2020.3022406 pmid:32894707 fatcat:qid525s3wzdfxdobo26y6fr3z4

Joint Layout Analysis, Character Detection and Recognition for Historical Document Digitization [article]

Weihong Ma, Hesuo Zhang, Lianwen Jin, Sihang Wu, Jiapeng Wang, Yongpan Wang
2020 arXiv   pre-print
In this paper, we propose an end-to-end trainable framework for restoring historical documents content that follows the correct reading order.  ...  We then use Hough transform for line detection on the binary mask and combine character results with the layout information to restore document content.  ...  [9] proposed a character attention generative adversarial network to create high visibility images from severely degraded or low visibility input images.  ... 
arXiv:2007.06890v1 fatcat:rb3re4ajxvgg5dq7gl7mvbovoi

Feature-Based Fusion Adversarial Recurrent Neural Networks for Text Sentiment Classification

Yaohong Ma, Hong Fan, Cheng Zhao
2019 IEEE Access  
To tackle these problems, we propose a Feature-Based Fusion Adversarial Recurrent Neural Networks (FARNN-Att) integrated model with an attention mechanism.  ...  Finally, a regularization method of adversarial training is used to improve the robustness and generalization ability of the model.  ...  ACKNOWLEDGMENTS The authors would like to thank the providers of the public datasets and the anonymous reviewers for their constructive comments.  ... 
doi:10.1109/access.2019.2940506 fatcat:ipgm3eqisfdujayrhthjv66doa

Text-DIAE: Degradation Invariant Autoencoders for Text Recognition and Document Enhancement [article]

Mohamed Ali Souibgui, Sanket Biswas, Andres Mafla, Ali Furkan Biten, Alicia Fornés, Yousri Kessentini, Josep Lladós, Lluis Gomez, Dimosthenis Karatzas
2022 arXiv   pre-print
Each of the pre-text objectives is specifically tailored for the final downstream tasks. We conduct several ablation experiments that show the importance of each degradation for a specific domain.  ...  In this work, we propose Text-Degradation Invariant Auto Encoder (Text-DIAE) aimed to solve two tasks, text recognition (handwritten or scene-text) and document image enhancement.  ...  Other state-of-the-art techniques [37, 69, 70, 80] used conditional-Generative Adversarial Network (c-GAN) based approaches to design a generator which produces the enhanced version of the document while  ... 
arXiv:2203.04814v3 fatcat:w7vbzopsxngu7njknd6a2n7shi

DeepErase: Weakly Supervised Ink Artifact Removal in Document Text Images [article]

W. Ronny Huang, Yike Qi, Qianqian Li, Jonathan Degange
2020 arXiv   pre-print
Paper-intensive industries like insurance, law, and government have long leveraged optical character recognition (OCR) to automatically transcribe hordes of scanned documents into text strings for downstream  ...  We devise a method to programmatically assemble real text images and real artifacts into realistic-looking "dirty" text images, and use them to train an artifact segmentation network in a weakly supervised  ...  The results discussed in this letter and references to terms architecture, robustness, efficient, accurate, and bias are with respect to the letters mathematical treatment of a generalized methodology  ... 
arXiv:1910.07070v3 fatcat:acann2xosndwddx2kqlseuehwa

DeepErase: Weakly Supervised Ink Artifact Removal in Document Text Images

Yike Qi, W. Ronny Huang, Qianqian Li, Jonathan L. DeGange
2020 2020 IEEE Winter Conference on Applications of Computer Vision (WACV)  
Paper-intensive industries like insurance, law, and government have long leveraged optical character recognition (OCR) to automatically transcribe hordes of scanned documents into text strings for downstream  ...  We devise a method to programmatically assemble real text images and real artifacts into realistic-looking "dirty" text images, and use them to train an artifact segmentation network in a weakly supervised  ...  The historical document text characters in [16] are printed while the annotations are handwritten, and the annotations have a slightly different shade, both of which are telltale signs for the network  ... 
doi:10.1109/wacv45572.2020.9093532 dblp:conf/wacv/QiHLD20 fatcat:zfu5o6s7lreavb2p22jmyiyz4a

An enhanced binarization framework for degraded historical document images

Wei Xiong, Lei Zhou, Ling Yue, Lirong Li, Song Wang
2021 EURASIP Journal on Image and Video Processing  
It uses a disk-shaped structuring element, whose radius is computed by the minimum entropy-based stroke width transform (SWT).  ...  AbstractBinarization plays an important role in document analysis and recognition (DAR) systems.  ...  [42] propose a supervised binarization for historical document images based on hierarchical deep supervised networks (DSNs).  ... 
doi:10.1186/s13640-021-00556-4 fatcat:aawmkhjf3ngs3bb3zbyyi4xz5q

Warped Document Image Correction Based on Checkboard Pattern and Geometric Transformation

Marian Labib, Khalid Amin, mina ibrahim
2021 IJCI. International Journal of Computers and Information  
OCR (Optical Character Recognition) error metrics are also used to gauge the success of the suggested approach.  ...  Document image warping problem refers to the process of geometrically transforming 2D images. In this work we aim to solve the warped document image problems.  ...  Generative Adversarial Network (CGAN) and Pix2pix networks [35] fail to produce the document of size of 256x256.  ... 
doi:10.21608/ijci.2021.53176.1036 fatcat:bcvzyf557zfrnasc2djynymp6y

An Operational Framework for Resilience

Jerome H. Kahan, Andrew C. Allen, Justin K. George
2009 Journal of Homeland Security and Emergency Management  
A visually direct technique for assisting resilience planners is to establish a "resilience profile" for key functions within critical systems.  ...  This article offers an operational framework that can prove useful to the Department of Homeland Security (DHS) and stakeholders at all levels, both public and private, as a basis for incorporating resilience  ...  Adversary Attack Path: This provides a graphical depiction of essential steps and stages included in a generic terrorist attack scenario.  ... 
doi:10.2202/1547-7355.1675 fatcat:j6pgrrlfoff6ln6rim5gzrsjge

A Roadmap for Big Model [article]

Sha Yuan, Hanyu Zhao, Shuai Zhao, Jiahong Leng, Yangxiao Liang, Xiaozhi Wang, Jifan Yu, Xin Lv, Zhou Shao, Jiaao He, Yankai Lin, Xu Han (+88 others)
2022 arXiv   pre-print
At the end of this paper, we conclude the further development of BMs in a more general view.  ...  With the rapid development of deep learning, training Big Models (BMs) for multiple downstream tasks becomes a popular paradigm.  ...  Caffe is good for general purpose convolutional neural networks but may not be a good option for recurrent networks due to insufficient relevant documentation.  ... 
arXiv:2203.14101v4 fatcat:rdikzudoezak5b36cf6hhne5u4

Cyberspace of the Fourth Scientific and Technological Revolution

Oleg N. Yanitsky
2019 International Journal of Social Research  
Historically speaking, to a certain limit the nature was capable to restore its functioning to some degree.  ...  An impact of cyberspace in general and cyberwars in particular on human behavior deserves a special attention.  ... 
doi:10.28933/ijsr-2019-01-2805 fatcat:fpuhw2ratvaejislgltdowyswi

Collective memory as a resource in Russian information warfare against Latvia

Jānis Krēķis
2015 Journalism Research  
In the network society power elite does not consist only of governments, but also of non-governmental sector. 16 Furthermore, the US Department of Defence now characterizes information operations as  ...  , waged between competitors, adversaries or enemies using information means to achieve their objectives". 8 Nevertheless, for M.  ... 
doi:10.15388/zt/jr.2015.8.8844 fatcat:ky5nabl76fdunksov7zxxitmwu
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