Image Retrieval Using Object Semantic Aggregation Histogram-Reference-Cited by-同舟云学术

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Image Retrieval Using Object Semantic Aggregation Histogram

Published:2023-05-25 Issue:5 Volume:15 Page:1736-1747
ISSN:1866-9956
Container-title:Cognitive Computation
language:en
Short-container-title:Cogn Comput

Author:

Lu Fen^ORCID,Liu Guang-Hai^ORCID

Funder

the National Natural Science Foundation of China

the Foundation of Development Research Centre of Guangxi in Humanities and Social Sciences

Publisher

Springer Science and Business Media LLC

Subject

Cognitive Neuroscience,Computer Science Applications,Computer Vision and Pattern Recognition

Link

https://link.springer.com/content/pdf/10.1007/s12559-023-10143-6.pdf

Reference25 articles.

1. Li X, Yang J, Ma J. Recent developments of content-based image retrieval (CBIR). Neurocomputing. 2021;452:675–89.

2. Kalantidis Y, Mellina C, Osindero S. Cross-dimensional weighting for aggregated deep convolutional features. Proc Eur Conf Comput Vis. 2016;685–701.

3. Zhu J, Wang J, Pang S, Guan W, Li Z, Li Y, et al. Co-weighting semantic convolutional features for object retrieval. J Vis Commun Image Represent. 2019;62:368–80.

4. Xu J, Wang C, Qi C, Shi C, Xiao B. Unsupervised semantic-based aggregation of deep convolutional features. IEEE Trans Image Process. 2019;28(2):601–11.

5. Lu F, Liu G-H. Image retrieval using contrastive weight aggregation histograms. Digit Signal Process. 2022;123:103457.

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