From Knowledge based Vision Systems to Cognitive Vision Systems: A Review - Publikacja - MOST Wiedzy

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From Knowledge based Vision Systems to Cognitive Vision Systems: A Review

Abstrakt

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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Kategoria:
Aktywność konferencyjna
Typ:
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Tytuł wydania:
Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 22nd International Conference, KES-2018, Belgrade, Serbia strony 1855 - 1864
Język:
angielski
Rok wydania:
2018
Opis bibliograficzny:
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:
Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1016/j.procs.2018.08.077
Weryfikacja:
Politechnika Gdańska

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