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Table 3: Comparison of the accuracy of our approach with methods from the state of the art.
Methods MSRC v1 Wang Holidays UKB
BoVW (Csurka et al., 2004) 0.48 0.41 0.50 2.95
SaCoCo(Iakovidou et al., 2019) - 0.51 0.76 3.33
CEDD (Chatzichristofis and Boutalis, 2008) - 0.54 0.72 3.24
VLAD (J
´
egou et al., 2010) - - 0.53 3.17
N-Gram (Pedrosa and Traina, 2013) - 0.34 - -
Grid (Ouni et al., 2021) 0.67 0.62 0.64 3.57
Fisher (Perronnin and Dance, 2007) - - 0.69 3.07
Ours 0.69 0.65 0.68 3.61
4 CONCLUSION
In this paper, we present an effective bag of visual
phrase model dependent on grouping approach. We
show that the utilization of density clustering ap-
proach joined with BoVW model increment the CBIR
precision. Utilizing two descriptors (KAZE, SURF),
our methodology accomplish a superior outcomes
compared to the state of the art methods.
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