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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Bibliographic Details
Main Author: Mishra, Puneet (author)
Other Authors: Passos, Dário (author)
Format: article
Language:eng
Published: 2021
Subjects:
1D-CNN
Neural networks
Fruit quality
Ensemble pre-processing
Artificial intelligence
Online Access:http://hdl.handle.net/10400.1/15488
Country:Portugal
Oai:oai:sapientia.ualg.pt:10400.1/15488

Internet

http://hdl.handle.net/10400.1/15488

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