Multi-output 1-dimensional convolutional neural networks for simultaneous prediction of different traits of fruit based on near-infrared spectroscopy

An automated deep learning pipeline based on advanced optimisations for leveraging spectral classification modelling

(2021) Dário Passos et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Nondestructive simultaneous prediction of internal browning disorder and quality attributes in ‘Rocha’ pear (Pyrus communis L.) using VIS-NIR spectroscopy

(2021) Sandra Cruz et al.   POSTHARVEST BIOLOGY AND TECHNOLOGY

A deep learning based regression method on hyperspectral data for rapid prediction of cadmium residue in lettuce leaves

(2020) Zhou Xin et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Understanding the learning mechanism of convolutional neural networks in spectral analysis

(2020) Xiaolei Zhang et al.   ANALYTICA CHIMICA ACTA

Visible-NIR ‘point’ spectroscopy in postharvest fruit and vegetable assessment: The science behind three decades of commercial use

(2020) Kerry B. Walsh et al.   POSTHARVEST BIOLOGY AND TECHNOLOGY

Improving moisture and soluble solids content prediction in pear fruit using near-infrared spectroscopy with variable selection and model updating approach

(2020) Puneet Mishra et al.   POSTHARVEST BIOLOGY AND TECHNOLOGY

Sequential fusion of information from two portable spectrometers for improved prediction of moisture and soluble solids content in pear fruit

(2020) Puneet Mishra et al.   TALANTA

DeepSpectra: An end-to-end deep learning approach for quantitative spectral analysis

(2019) Xiaolei Zhang et al.   ANALYTICA CHIMICA ACTA

Convolutional neural network for simultaneous prediction of several soil properties using visible/near-infrared, mid-infrared, and their combined spectra

(2019) Wartini Ng et al.   GEODERMA

Fine-tuning convolutional neural network with transfer learning for semantic segmentation of ground-level oilseed rape images in a field with high weed pressure

(2019) Alwaseela Abdalla et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Multivariate calibration of spectroscopic sensors for postharvest quality evaluation: A review

(2019) Wouter Saeys et al.   POSTHARVEST BIOLOGY AND TECHNOLOGY

Non-invasive measurements of ‘Yunhe’ pears by vis-NIRS technology coupled with deviation fusion modeling approach

(2019) Lei-Ming Yuan et al.   POSTHARVEST BIOLOGY AND TECHNOLOGY

Deep-learning-based regression model and hyperspectral imaging for rapid detection of nitrogen concentration in oilseed rape ( Brassica napus L. ) leaf

(2018) Xinjie Yu et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Modern practical convolutional neural networks for multivariate regression: Applications to NIR calibration

(2018) Chenhao Cui et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Development of deep learning method for predicting firmness and soluble solid content of postharvest Korla fragrant pear using Vis/NIR hyperspectral reflectance imaging

(2018) Xinjie Yu et al.   POSTHARVEST BIOLOGY AND TECHNOLOGY

One-dimensional convolutional neural networks for spectroscopic signal regression

(2017) Salim Malek et al.   JOURNAL OF CHEMOMETRICS

Assessing firmness and SSC of pears based on absorption and scattering properties using an automatic integrating sphere system from 400 to 1150 nm

(2016) Xueming He et al.   POSTHARVEST BIOLOGY AND TECHNOLOGY

Application of NIRS for predicting fatty acids in intramuscular fat of rabbit

(2012) C. Zomeño et al.   MEAT SCIENCE

Effect of fruit moving speed on predicting soluble solids content of ‘Cuiguan’ pears (Pomaceae pyrifolia Nakai cv. Cuiguan) using PLS and LS-SVM regression

(2008) Tong Sun et al.   POSTHARVEST BIOLOGY AND TECHNOLOGY