CBIR-ANR: A content-based image retrieval with accuracy noise reduction-Reference-Cited by-同舟云学术

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CBIR-ANR: A content-based image retrieval with accuracy noise reduction

Published:2023-03 Issue: Volume:15 Page:100486
ISSN:2665-9638
Container-title:Software Impacts
language:en
Short-container-title:Software Impacts

Author:

Vieira Gabriel S.^ORCID,Fonseca Afonso U.,Soares Fabrizzio

Publisher

Elsevier BV

Subject

Software

Reference22 articles.

1. A survey of tag-based information retrieval;Lee;Int. J. Multimedia Inf. Retr.,2017

2. Image retrieval based on a multi-integration features model;Chu;Math. Probl. Eng.,2020

3. A novel image retrieval method based on multi-features fusion;Niu;Signal Process., Image Commun.,2020

4. Image retrieval using the intensity variation descriptor;Wei;Math. Probl. Eng.,2020

5. A novel image retrieval based on visual words integration of SIFT and SURF;Ali;PLoS One,2016

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Efficient Video Frames Retrieval System Using Speeded Up Robust Features Based Bag of Visual Words;ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal;2023-12-29

2. A novel content-based image retrieval system with feature descriptor integration and accuracy noise reduction;Expert Systems with Applications;2023-12

3. An Extended Canberra Similarity Measure Method for Content-Based Image Retrieval;2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT);2023-10-20

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