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# Trained CCN for microalgal pigment spectrophotometric quantification
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Repository hosting the trained CNNs associated with the article (availablme in open access):
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[A deep learning framework for spectrophotometric quantification of key microalgal pigments.](https://www.sciencedirect.com)
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Bayomie, O., & Pozzobon, V. (2026).
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*Machine Learning with Applications*.
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## Structure
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It contains the optimized model (stored as an .h5 file) for lutein and zeaxanthin (hybrid architecture). In addition, the different models reported in Table 3 of the article are uploaded in the folder *Table_3_Models*.
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## Contact
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Please feel free to contact me. You can find my details on: https://victorpozzobon.github.io/
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# Trained CCN for microalgal pigment spectrophotometric quantification
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Repository hosting the trained CNNs associated with the article (availablme in open access):
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[A deep learning framework for spectrophotometric quantification of key microalgal pigments.](https://www.sciencedirect.com/science/article/pii/S2666827026000447)
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Bayomie, O., & Pozzobon, V. (2026).
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*Machine Learning with Applications*, 100879.
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## Structure
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It contains the optimized model (stored as an .h5 file) for lutein and zeaxanthin (hybrid architecture). In addition, the different models reported in Table 3 of the article are uploaded in the folder *Table_3_Models*.
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Predictions for lutein
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## Contact
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Please feel free to contact me. You can find my details on: https://victorpozzobon.github.io/
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