Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/1972
Title: Generalized Class Representative Computation with Graph Embedding and Clustering
Other Titles: Genelleştirilmiş Çizge Gömme ve Öbekleme İle Sınıf Temsilcisi Çıkarma
Authors: Aydos, Fahri
Demirci, Muhammed Fatih
143569
Keywords: class representative
object recognition
graph embedding
clustering
Issue Date: 2015
Publisher: IEEE
Source: Aydos, F., & Demirci, M. F. (2015, May). Generalized class representative computation with graph embedding and clustering. In 2015 23nd Signal Processing and Communications Applications Conference (SIU) (pp. 2525-2528). IEEE.
Abstract: In this paper, we propose an object category representation framework by first showing objects as graph structures and embedding graphs into vector spaces for color object recognition. The object categories are then built by clustering. The distance between an object and an object category is computed by Earth Mover's Distance. The proposed method has been successfully evaluated on a number of datasets, and its performance has been computed against previous techniques.
Description: 23nd Signal Processing and Communications Applications Conference (SIU) (2015 : Malatya, TURKEY)
URI: https://ieeexplore.ieee.org/document/7130398
https://hdl.handle.net/20.500.11851/1972
ISBN: 978-1-4673-7386-9
ISSN: 2165-0608
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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