A New Language-Independent Deep CNN for Scene Text Detection and Style Transfer in Social Media Images-Reference-Cited by-同舟云学术

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A New Language-Independent Deep CNN for Scene Text Detection and Style Transfer in Social Media Images

Published:2023 Issue: Volume:32 Page:3552-3566
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Shivakumara Palaiahnakote¹^ORCID,Banerjee Ayan²^ORCID,Pal Umapada²^ORCID,Nandanwar Lokesh¹,Lu Tong³^ORCID,Liu Cheng-Lin⁴^ORCID

Affiliation:

1. Department of Computer System and Technology, Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia

2. Indian Statistical Institute, Kolkata, India

3. Department of Computer Science and Technology, Nanjing University, Nanjing, China

4. National Laboratory of Pattern Recognition, Institute of Automation of Chinese Academy of Sciences, Beijing, China

Funder

Ministry of Higher Education of Malaysia for the Generous Grant Fundamental Research Grant Scheme

Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9991910/10159272.pdf?arnumber=10159272

Reference65 articles.

1. GA-DAN: Geometry-Aware Domain Adaptation Network for Scene Text Detection and Recognition

2. HindEnCorp—Hindi-English and Hindi-only corpus for machine translation;bojar;Proc Int Conf Lang Resour Eval (LREC),2014

3. Convolutional Character Networks

4. Dual Attention Network for Scene Segmentation

5. Geometry Normalization Networks for Accurate Scene Text Detection

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