Training deep network models for accurate recognition of texts in scene images
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 accur...
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2021
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sg-ntu-dr.10356-1484862021-05-04T05:00:03Z Training deep network models for accurate recognition of texts in scene images Chen, Pengfei Lu Shijian School of Computer Science and Engineering Shijian.Lu@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Engineering::Computer science and engineering::Computing methodologies::Document and text processing 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. Bachelor of Engineering (Computer Science) 2021-05-04T05:00:02Z 2021-05-04T05:00:02Z 2021 Final Year Project (FYP) 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 https://hdl.handle.net/10356/148486 en PSCSE19-0039 application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Engineering::Computer science and engineering::Computing methodologies::Document and text processing Chen, Pengfei Training deep network models for accurate recognition of texts in scene images |
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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. |
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Lu Shijian |
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Lu Shijian Chen, Pengfei |
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Final Year Project |
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Chen, Pengfei |
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Chen, Pengfei |
title |
Training deep network models for accurate recognition of texts in scene images |
title_short |
Training deep network models for accurate recognition of texts in scene images |
title_full |
Training deep network models for accurate recognition of texts in scene images |
title_fullStr |
Training deep network models for accurate recognition of texts in scene images |
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Training deep network models for accurate recognition of texts in scene images |
title_sort |
training deep network models for accurate recognition of texts in scene images |
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Nanyang Technological University |
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2021 |
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https://hdl.handle.net/10356/148486 |
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