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Cross-model retrieval with deep learning for business application
Wang, Yufei1; Wang, Huanting2,3; Yang, Jiating2; Chen, Jianbo3
2021-03-09
Conference Name2020 7th International Conference on Computer-Aided Design, Manufacturing, Modeling and Simulation, CDMMS 2020
Source Publication7th International Conference on Computer-Aided Design, Manufacturing, Modeling and Simulation, CDMMS 2020 - 2. Algorithm Design and Computational Science
Volume1802
Issue3
Conference Date2020-11-14
Conference PlaceBusan, Korea, Republic of
PublisherIOP Publishing Ltd
Contribution Rank2
Abstract

Cross-modal retravel has been used in many fields, such as business and search engines. Most search engines for business are text-based, but text-based search engines are limited by equipment and the strict requirement for knowledge. Text-based search needs keyboards to finish the search process, which requires users to have the knowledge of using keyboards. Compared to the text-based search, audio-based search has advantages. First, it avoids the traditional ways of inputting information. And it gets rid of the gap in time between inputting information for searching and getting useful information. In this paper, we propose a way to use audio to search images for business applications. We use deep learning to implement cross-modal retrieval systems between images and audio. We first extract features from images and audio respectively. And then we implement a neural network with two identical networks to learn the correspondence between images and audio. The first network extracts the features from images and audio further for calculation, and the second network learns whether two features from different modalities are related. This research provides a new way for business applications to search for information more instantly. © Published under licence by IOP Publishing Ltd.

KeywordCross-modal retrieval Audio features Deep hashing Useful information
Department光谱成像技术研究室
DOI10.1088/1742-6596/1802/3/032035
Indexed ByEI
Language英语
ISSN17551307;17551315
EI Accession Number20211210123555
Citation statistics
Document Type会议论文
Identifierhttp://ir.opt.ac.cn/handle/181661/94577
Collection光谱成像技术研究室
Corresponding AuthorYang, Jiating
Affiliation1.Simon Fraser University, 8888 University Dr, Bumaby; BC; V5A 1S6, Canada
2.Xian Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xian, China
3.University of Chinese Academy of Sciences, Beijing; 100049, China
Recommended Citation
GB/T 7714
Wang, Yufei,Wang, Huanting,Yang, Jiating,et al. Cross-model retrieval with deep learning for business application[C]:IOP Publishing Ltd,2021.
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