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An improved similarity matching model for the content-based image retrieval model

Open Access
|Jul 2025

Figures & Tables

Figure 1:

General workflow of CBIR.
General workflow of CBIR.

Figure 2:

Sample query image.
Sample query image.

Figure 3:

Result comparisons with different algorithms on the ROxford dataset. EP, equilibrium propagation; OHEM, optimized hybrid ensemble model.
Result comparisons with different algorithms on the ROxford dataset. EP, equilibrium propagation; OHEM, optimized hybrid ensemble model.

Figure 4:

Result comparisons with different algorithms on the RParis dataset. EP, equilibrium propagation; OHEM, optimized hybrid ensemble model.
Result comparisons with different algorithms on the RParis dataset. EP, equilibrium propagation; OHEM, optimized hybrid ensemble model.

Figure 5:

Comparison of computation time of different models on ROxford and RParis datasets. EP, equilibrium propagation; OHEM, optimized hybrid ensemble model.
Comparison of computation time of different models on ROxford and RParis datasets. EP, equilibrium propagation; OHEM, optimized hybrid ensemble model.

Comparison of precision and recall on the datasets

MethodROxford
RParis
PrecisionRecallF1-ScorePrecisionRecallF1-Score
CSM [18]83.297173.5884.2871.9378.83
EP [19]83.1270.171.4584.5672.0981.23
DCM [20]79.1265.161.4580.0969.0175.41
GA-based IR [21]84.1666.678.5685.567274.51
IRT [22]80.1469.571.2678.4168.4773.25
OHEM85.5673.381.4586.2575.5987.89
Language: English
Submitted on: Aug 30, 2024
Published on: Jul 19, 2025
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year

© 2025 Manimegalai Asokaraj, Josephine Prem Kumar, Nanda Ashwin, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.