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Details about the dataset have already been presented in Sect.
Overall, the clustering results based on the 3DZD for the odour dataset have been encouraging.
The similar images in Oxford dataset have much more overlap than those in the MSP dataset.
The images in the dataset have different sizes and therefore are not suitable for PCA directly.
Moreover, writers in this dataset have different genders, age ranges, and nationalities.
Images in this dataset have some similarities since they are from the same tracking sequence.
First, all models applied to the Wiki dataset have smaller runtime than the EHR dataset.
Experimental results with a real dataset have demonstrated that this CPIT model can be practically implemented and provide satisfactory results.
The final requisite is that attacks injected in the dataset have to represent a multi-step strategy.
In addition, corrupted events, less than 0.1% of the whole dataset, have been ignored or manually corrected.
After 100 training epochs, experiments on DCASE2016 dataset encounter overfitting problem; experiments on LITIS ROUEN dataset have almost converged.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com