Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorNur Muhamad Iqbal Abdul Sallim
dc.description.abstractGiven an image of an event or object, key information such as location, description and other attributes may not be ascertained purely by visual inspection. Usually, this image would be searched on the internet through a search engine and after perusing through various websites, the information required could be obtained. The integrity and accuracy of the information obtained can be further enhanced by cross-referencing across multiple resources or websites, unless a reputable or trustworthy website provides the necessary information. Images uploaded onto the internet are often tagged by the uploader which could be deemed useful if the tags provided are comprehensive and accurate. This provides textual metadata which are then used by search engines to provide results when a search is executed. There are various other methods of which an image is associated with other visually similar images or tags such as using colour features that correspond to other images with similar colour profiles [1]. The goal and objective of this project is to mimic the research and information that would be gathered by a human by using artificial intelligence (AI). The program or AI designed in this project would utilise Python programming language.en_US
dc.format.extent58 p.en_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titleKnowledge extraction from web imagesen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorMao Kezhien_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineering (Electrical and Electronic Engineering)en_US
item.fulltextWith Fulltext-
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
Files in This Item:
File Description SizeFormat 
Knowledge Extraction from Web Images.pdf
  Restricted Access
2.84 MBAdobe PDFView/Open

Page view(s)

Updated on Jan 26, 2021


Updated on Jan 26, 2021

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.