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. 2022 May 18;2022:6034971. doi: 10.1155/2022/6034971

Table 5.

Comparison of PFP-LHCINCA model with published results of other ultrasound-based fetal sex classification methods.

Study Method Dataset Best accuracy (%)
Maysanjaya et al. [7] Learning vector quantization, artificial vector quantization 64 males
25 females
63.0%

Aljuboori et al. [8] Fuzzy C-mean, discrete wavelet transform, local binary pattern, median, Laplacian filters 50 males
50 females
94.0%

PFP-LHCINCA Pyramidal fixed-size patch division, local phase quantization and histogram of oriented gradients based feature extraction, hybrid Chi2 and iterative neighborhood component analysis feature selection 339 males
332 females
99.11% (kNN classifier tuned with Bayesian optimizer)