Improving Deep Learning based Optical Character Recognition via Neural Architecture Search

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

5 Scopus Citations
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Author(s)

  • Zhenyao Zhao
  • Min Jiang
  • Shihui Guo
  • Zhenzhong Wang
  • Fei Chao

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publication2020 IEEE Congress on Evolutionary Computation (CEC)
Subtitle of host publication2020 CONFERENCE PROCEEDINGS
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Electronic)978-1-7281-6929-3
ISBN (Print)978-1-7281-6930-9
Publication statusPublished - Jul 2020

Publication series

NameIEEE Congress on Evolutionary Computation, CEC - Conference Proceedings

Conference

Title2020 IEEE Congress on Evolutionary Computation, CEC 2020
LocationVirtual
PlaceUnited Kingdom
CityGlasgow
Period19 - 24 July 2020

Abstract

Optical character rcecognition (OCR) is a process of converting images of typed, handwritten or printed text into machine-encoded one. In recent years, the methods represented by deep learning have greatly improved the performance of OCR systems, but the main challenges of such systems are 1) to accurately perform text detection in complex scenes and 2) to identify and set the optimal parameters to optimize the performance of the system. In this paper, we propose an OCR method based on Neural Architecture Search technique, called AutOCR. The characteristic of the proposed method is the automatic design of text detection framework using an evolutionary computation neural architecture search method. This design can not only accurately recognize the text in a complex environment, but also avoid the process of experts participating in parameter adjustment. We compared it with different methods, and the experimental results proved the effectiveness of our method.

Citation Format(s)

Improving Deep Learning based Optical Character Recognition via Neural Architecture Search. / Zhao, Zhenyao; Jiang, Min; Guo, Shihui; Wang, Zhenzhong; Chao, Fei; Tan, Kay Chen.

2020 IEEE Congress on Evolutionary Computation (CEC): 2020 CONFERENCE PROCEEDINGS. Institute of Electrical and Electronics Engineers, 2020. 9185798 (IEEE Congress on Evolutionary Computation, CEC - Conference Proceedings).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review