Knowledge extraction from images

Knowledge extraction is a process of knowledge creation from different types which are structured and unstructured of sources. Images belong to the group of unstructured sources. The extracted knowledge must be solid data that is in a readable format and interpretable format by machine or a given pr...

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Main Author: Wang, Yuqi
Other Authors: Mao Kezhi
Format: Final Year Project
Language:English
Published: 2016
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Online Access:http://hdl.handle.net/10356/67918
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-679182023-07-07T17:03:16Z Knowledge extraction from images Wang, Yuqi Mao Kezhi School of Electrical and Electronic Engineering DRNTU::Engineering Knowledge extraction is a process of knowledge creation from different types which are structured and unstructured of sources. Images belong to the group of unstructured sources. The extracted knowledge must be solid data that is in a readable format and interpretable format by machine or a given program used by end users achieving their purpose. Knowledge extraction from images aims to gain valuable information satisfying users’ requirements. With the development of technology, especially for Internet Industries, online image searching engines has arisen and improved for several years and led online searching technology to a new level. However, the precision and efficiency will be the most important parts for online image searching and needed to find ways to innovate and develop constantly. According to some existing machine learning theories and image processing principles, a refined search will be shown in this report for enhancing image search engines to think more like a human. The basic concept of such a thinking way is actually to combine two sub-steps of the process for extraction, one is extracting information and analysis from the image itself, the other one is extracting from text part tagged to the image, such as short descriptions or titles. The verification results demonstrate that the refined system will have an ideal and effective outcome and can be applied to real cases. Bachelor of Engineering 2016-05-23T07:12:15Z 2016-05-23T07:12:15Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/67918 en Nanyang Technological University 47 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering
spellingShingle DRNTU::Engineering
Wang, Yuqi
Knowledge extraction from images
description Knowledge extraction is a process of knowledge creation from different types which are structured and unstructured of sources. Images belong to the group of unstructured sources. The extracted knowledge must be solid data that is in a readable format and interpretable format by machine or a given program used by end users achieving their purpose. Knowledge extraction from images aims to gain valuable information satisfying users’ requirements. With the development of technology, especially for Internet Industries, online image searching engines has arisen and improved for several years and led online searching technology to a new level. However, the precision and efficiency will be the most important parts for online image searching and needed to find ways to innovate and develop constantly. According to some existing machine learning theories and image processing principles, a refined search will be shown in this report for enhancing image search engines to think more like a human. The basic concept of such a thinking way is actually to combine two sub-steps of the process for extraction, one is extracting information and analysis from the image itself, the other one is extracting from text part tagged to the image, such as short descriptions or titles. The verification results demonstrate that the refined system will have an ideal and effective outcome and can be applied to real cases.
author2 Mao Kezhi
author_facet Mao Kezhi
Wang, Yuqi
format Final Year Project
author Wang, Yuqi
author_sort Wang, Yuqi
title Knowledge extraction from images
title_short Knowledge extraction from images
title_full Knowledge extraction from images
title_fullStr Knowledge extraction from images
title_full_unstemmed Knowledge extraction from images
title_sort knowledge extraction from images
publishDate 2016
url http://hdl.handle.net/10356/67918
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