Image Search Engine by Deep Neural Networks

Conference Paper (2022)
Author(s)

Y. Yao (Student TU Delft)

Q. Zhang (Student TU Delft)

Y Hu (Student TU Delft)

C. Meo (TU Delft - Signal Processing Systems)

Y. Wang (TU Delft - Signal Processing Systems)

Andrea Nanetti (Nanyang Technological University)

J. Dauwels (TU Delft - Signal Processing Systems)

Research Group
Signal Processing Systems
Copyright
© 2022 Y. Yao, Q. Zhang, Y. HU, C. Meo, Y. Wang, Andrea Nanetti, J.H.G. Dauwels
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Y. Yao, Q. Zhang, Y. HU, C. Meo, Y. Wang, Andrea Nanetti, J.H.G. Dauwels
Research Group
Signal Processing Systems
Pages (from-to)
134
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Abstract

We typically search for images by keywords, e.g., when looking for images of apples, we would enter the word “apple” as query. However, there are limitations. For example, if users input keywords in a specific language, then they may miss results labeled in other languages. Moreover, users may have an image of the object they want to obtain more information about, e.g., a landmark, but they may not know the name of it. In such scenario, word-based search is not adequate, while imagebased search would be ideally suited. These needs drive us to develop a purely content-based image search engine, meaning that users can search images with an image as query. Motivated by this use case with numerous applications, in this paper we propose and validate an image query based search engine...

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