A synergistic use of chemometrics and deep learning improved the predictive performance of near-infrared spectroscopy models for dry matter prediction in mango fruit
This study provides an innovative approach to improve deep learning (DL) models for spectral data processing with the use of chemometrics knowledge. The technique proposes pre-filtering the outliers using the Hotelling’s T2 and Q statistics obtained with partial least-square (PLS) analysis and spect...
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| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2021
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| Texto completo: | http://hdl.handle.net/10400.1/15488 |
| País: | Portugal |
| Oai: | oai:sapientia.ualg.pt:10400.1/15488 |