Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/148486
Title: Training deep network models for accurate recognition of texts in scene images
Authors: Chen, Pengfei
Keywords: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Engineering::Computer science and engineering::Computing methodologies::Document and text processing
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Chen, P. (2021). Training deep network models for accurate recognition of texts in scene images. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/148486
Project: PSCSE19-0039
Abstract: Recognition of text automatically is playing an important role and act as a foundation in Artificial Intelligence field. In the previous decade, researchers are struggle on overcoming the complicity in their pipeline. With applying deep learning in text recognition, the overall performance and accuracy improved greatly. In this FYP, the state of art deep learning models for text recognition, CRNN and ASTER, will be implemented and trained. For optimal performance, multiple hyperparameter will be tuned. During the chapter of methodology, the issues people might face will be discussed and ways for solving the issues will be provided. The model performance on various datasets will be evaluated and showed in this report.
URI: https://hdl.handle.net/10356/148486
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
FYP Report Chen Peng Fei.pdf
  Restricted Access
1.67 MBAdobe PDFView/Open

Page view(s)

159
Updated on May 17, 2022

Download(s) 50

23
Updated on May 17, 2022

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.