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A Computational Approach towards Visual Object Recognition at Taxonomic Levels of Concepts
المؤلفون المشاركون
Araabi, Babak N.
Nili Ahmadabadi, Majid
Sadeghi, Zahra
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-06-22
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
It has been argued that concepts can be perceived at three main levels of abstraction.
Generally, in a recognition system, object categories can be viewed at three levels of taxonomic hierarchy which are known as superordinate, basic, and subordinate levels.
For instance, “horse” is a member of subordinate level which belongs to basic level of “animal” and superordinate level of “natural objects.” Our purpose in this study is to take an investigation into visual features at each taxonomic level.
We first present a recognition tree which is more general in terms of inclusiveness with respect to visual representation of objects.
Then we focus on visual feature definition, that is, how objects from the same conceptual category can be visually represented at each taxonomic level.
For the first level we define global features based on frequency patterns to illustrate visual distinctions among artificial and natural.
In contrast, our approach for the second level is based on shape descriptors which are defined by recruiting moment based representation.
Finally, we show how conceptual knowledge can be utilized for visual feature definition in order to enhance recognition of subordinate categories.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Sadeghi, Zahra& Araabi, Babak N.& Nili Ahmadabadi, Majid. 2015. A Computational Approach towards Visual Object Recognition at Taxonomic Levels of Concepts. Computational Intelligence and Neuroscience،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1057778
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Sadeghi, Zahra…[et al.]. A Computational Approach towards Visual Object Recognition at Taxonomic Levels of Concepts. Computational Intelligence and Neuroscience No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1057778
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Sadeghi, Zahra& Araabi, Babak N.& Nili Ahmadabadi, Majid. A Computational Approach towards Visual Object Recognition at Taxonomic Levels of Concepts. Computational Intelligence and Neuroscience. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1057778
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1057778
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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