Deep Features for Text Spotting
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Deep learning has advanced text spotting by learning more representative features, devising better representation of text proposals, and using large-scale synthetic datasets.
“Deep learning has advanced this area by learning more representative feature [87], devising better representation of text proposals [88], and using large-scale synthetic dataset [89].”
From Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things (2021) · cites this paper as [87]
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- Authors
- Jaderberg, M., Vedaldi, A., & Zisserman, A.
- Affiliations
- University of Oxford (GB)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2014
- Pages
- 512-528
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W70975097
- Cited by
- 653
- References
- 51
- Citations by year
- 2026: 6 · 2025: 16 · 2024: 19 · 2023: 24 · 2022: 35 · 2021: 73 · 2020: 76 · 2019: 98 · 2018: 98 · 2017: 91 · 2016: 72 · 2015: 39 · 2014: 6
- FWCI
- 37.28
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Handwritten Text Recognition Techniques
- Physical Sciences › Engineering › Media Technology › Vehicle License Plate Recognition
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Keywords
- text spotting, text detection, text recognition, convolutional neural networks
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