A powerful method for interactive content-based image retrieval by variable compressed convolutional info neural networks
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s00371-023-03104-5.pdf
Reference71 articles.
1. Chhabra, P., Garg, N.K., Kumar, M.: Content-based image retrieval system using ORB and SIFT features. Neural. Comput. Appl. 32(7), 2725–2733 (2020)
2. Sathiamoorthy, S., Natarajan, M.: An efficient content-based image retrieval using enhanced multi-trend structure descriptor. SN Appl. Sci. 2(2), 1–20 (2020)
3. Pradhan, J., Ajad, A., Pal, A.K., Banka, H.: Multi-level colored directional motif histograms for content-based image retrieval.Visual Comput. 36(9), 1847-1868 (2020).
4. Mistry, Y., Ingole, D.T., Ingole, M.D.: Content based image retrieval using hybrid features and various distance metric. J. Electr. Syst. Inf. Technol. 5(3), 874–888 (2018)
5. Chavda, S., Goyani, M.: Hybrid approach to content-based image retrieval using modified multi-scale LBP and color features. SN Comput. Sci. 1(6), 1–5 (2020)
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