Supplementary data and algorithms associated with the article of deep learning for predicting TVC in peeled shrimp

Python codes:
1.SAEs.py #this file is used to train the SAEs model
2.SAEs-PLSR.py #use this file to train PLSR model based on deep spectra features, and evaluate the model.
3.SPA-PLSR.py #use this file to train PLSR model based on characteristic wavelengths selected by SPA, and evaluate the model.
4.F-PLSR.py #use this file to train PLSR model based on full spectra, and evaluate the model.
Data:
1.ramdonpixel_1.pkl #60060 spectra for training SAEs model
2.ramdonpixel_2.pkl #60060 spectra for validating SAEs model
3.Fullspectra.csv #200 samples with 230 bands spectra and reference TVC values
4.SPAspectra.csv #200 samples with 18 characteristic wavelengths and reference TVC values
Logs:
saved model files
Results:
experimental results files