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Abstract
Computer vision research and applications have their origins in 1960s. Limitations in computational resources inherent of that time, among other reasons, caused research to move away from artificial intelligence and generic recognition goals to accomplish simple tasks for constrained scenarios. In the past decades, the development in machine learning techniques has contributed to noteworthy progress in vision systems. However, most applications rely on purely bottom-up approaches that require large amounts of training data and are not able to generalize well for novel data. In this work, we survey knowledge associated to Computer Vision Systems developed in the last ten years. It is seen that the use of explicit knowledge has contributed to improve several computer vision tasks. The integration of explicit knowledge with image data enables the development of applications that operate on a joint bottom-up and top-down approach to visual learning, analogous to human vision. Knowledge associated to vision systems is shown to have less dependency on data, increased accuracy, and robustness.
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Authors (4)
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Thamiris Souza
- University of Newcastle, Australia
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Caterine De
- University of Newcastle, Australia
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Cesar Sanin
- University of Newcastle, Australia
Cite as
Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1016/j.procs.2018.08.077
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Details
- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Title of issue:
- Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 22nd International Conference, KES-2018, Belgrade, Serbia strony 1855 - 1864
- Language:
- English
- Publication year:
- 2018
- Bibliographic description:
- Souza T., De C., Sanin C., Szczerbicki E.: From Knowledge based Vision Systems to Cognitive Vision Systems: A Review// Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 22nd International Conference, KES-2018, Belgrade, Serbia/ ed. Robert J. Howlett, Carlos Toro, Yulia Hicks, Lakhmi C. Jain : , 2018, s.1855-1864
- DOI:
- Digital Object Identifier (open in new tab) 10.1016/j.procs.2018.08.077
- Verified by:
- Gdańsk University of Technology
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