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Language: enSubject: semantic content extraction

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  • Thumbnail Image
    Conference Object
    A Component-Based Object Detection Method Extended With a Fuzzy Inference Engine
    (Ieee, 2015) Koyuncu, Murat; Cetinkaya, Basar
    In this paper, we propose a component-based object detection method extended with the fuzzy inference technique. The proposed method detects constituent components of a complex object instead of a whole object in images. For component detection, multiple multi-class support vector machines (SVM) are used in parallel. Each SVM classifies the candidate component using a different low-level image feature. The obtained results are fused to reach a decision about the component. Then, a fuzzy object extractor determines the whole object considering the detected components and their geometric configurations. The fuzzy object extractor is a fuzzy inference engine which tests various combinations of detected components and their fuzzified directions and distances. The initial tests yield promising results and encourage further studies to extend proposed method.
  • Thumbnail Image
    Conference Object
    A Component-Based Object Detection Method Extended With a Fuzzy Inference Engine
    (Institute of Electrical and Electronics Engineers Inc., 2015) Koyuncu,M.; Cetinkaya,B.
    In this paper, we propose a component-based object detection method extended with the fuzzy inference technique. The proposed method detects constituent components of a complex object instead of a whole object in images. For component detection, multiple multi-class support vector machines (SVM) are used in parallel. Each SVM classifies the candidate component using a different low-level image feature. The obtained results are fused to reach a decision about the component. Then, a fuzzy object extractor determines the whole object considering the detected components and their geometric configurations. The fuzzy object extractor is a fuzzy inference engine which tests various combinations of detected components and their fuzzified directions and distances. The initial tests yield promising results and encourage further studies to extend proposed method. © 2015 IEEE.