Object relationship network model for image collections이미지 집합의 분석을 위한 사물 관계 네트워크 모델

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Image collections are indispensable parts of all image-based research. It is widely used for knowledge-training, comparing performance between systems, or verifying the effectiveness of the algorithms. Its role is not just source data of training, but it can affect performance and even can restrict focal planes of the image processing field. Various image datasets have appeared since PASCAL and Caltech-101, but there are few ways to verify the datasets themselves. This paper suggests the model that describes the collection of multiple images, based on the relationship between occurred objects in the images. Namely, object-relation network model for image collections. Recent image collections consist of dozens-GB data with a massive number of color pixels. It means it is practically impossible to compare the image collections directly, or even, to grasp properties of the individual collection. The model can work as single common criteria to evaluate the image collections.
Advisors
Choi, Sungheeresearcher최성희researcher
Description
한국과학기술원 :전산학부,
Publisher
한국과학기술원
Issue Date
2016
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 전산학부, 2016.2 ,[iv, 19 p. :]

Keywords

Visual Database; Knowledge graph; Image analysis; Computer Vision; Image object; 이미지 분석; 지식 그래프; 컴퓨터 비전; 사물 기반 이미지 분석; 시맨틱

URI
http://hdl.handle.net/10203/221900
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=649671&flag=dissertation
Appears in Collection
CS-Theses_Master(석사논문)
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