A Systematic Literature Review of Deep Learning Approaches for Sketch-Based Image Retrieval: Datasets, Metrics, and Future Directions-Reference-Cited by-同舟云学术

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A Systematic Literature Review of Deep Learning Approaches for Sketch-Based Image Retrieval: Datasets, Metrics, and Future Directions

Published:2024 Issue: Volume:12 Page:14847-14869
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Yang Fan¹^ORCID,Ismail Nor Azman¹^ORCID,Pang Yee Yong¹,Kebande Victor R.²^ORCID,Al-Dhaqm Arafat³,Koh Tieng Wei³^ORCID

Affiliation:

1. Faculty of Computing, Universiti Teknologi Malaysia (UTM), Skudai, Johor, Malaysia

2. Department of Computer Science (DIDA), Blekinge Institute of Technology, Karlskrona, Sweden

3. Computer and Information Sciences Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Perak, Malaysia

Funder

Blekinge Institute of Technology, Sweden, through the Grant Funded Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10413476.pdf?arnumber=10413476

Reference143 articles.

1. Text-based, content-based, and semantic-based image retrievals: A survey;Alkhawlani;Int. J. Comput. Inf. Technol.,2015

2. Text-Based Image Retrieval Using Deep Learning

3. Content-based image retrieval at the end of the early years

4. Deep Learning for Content-Based Image Retrieval

5. Information fusion in content based image retrieval: A comprehensive overview

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