Document analysis systems that improve with use
| Autor: | George Nagy |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Data exploration
Information retrieval Computer science 020207 software engineering Mistake 02 engineering and technology Document analysis Computer Science Applications Handwriting Typeface 0202 electrical engineering electronic engineering information engineering Classification methods Image acquisition 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Imperfect Software |
| Zdroj: | International Journal on Document Analysis and Recognition (IJDAR). 23:13-29 |
| ISSN: | 1433-2825 1433-2833 |
| DOI: | 10.1007/s10032-019-00344-x |
| Popis: | Document analysis tasks for which representative labeled training samples are available have been largely solved. The next frontier is coping with hitherto unseen formats, unusual typefaces, idiosyncratic handwriting and imperfect image acquisition. Adaptive and style-constrained classification methods can overcome some expected variability, but human intervention will remain necessary in many tasks. Interactive pattern recognition includes data exploration and active learning as well as access to stored documents. The principle of “green interaction” is to make use of every intervention to reduce the likelihood that the automated system will make the same mistake again and again. Some of these techniques may pop up in forthcoming personal camera-based memex-like applications that will have a far broader range of input documents and scene text than the current, successful but highly specialized, systems for patents, postal addresses, bank checks and books. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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