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We implement our model using the MatConvNet package [33].
We implement the proposed model using the MatConvNet package [24].
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During the experiments, we implement the verification network and the identification network using the MatConvNet [42] package, and utilize the ResNet-50 [41] network as the CNN model for training and testing.
The statistical analysis were performed using the R statistical package and the effsize package (Torchiano 2017).
Data were analyzed using the R package.
Solubility and supersaturation were calculated using the software package EQ3/6.
The estimation was performed in R using the strucchange package.
All plots are generated using the R package ggplot2 [40].
Data were analysed using the Statistical Package for Social Sciences SPSSS 17.0).
It was conducted using the lme4 package in R [82].
The computation was implemented using the R package "agRee" [13].
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