Mid-infrared spectra feature extraction and visualization by convolutional neural network for sugar adulteration identification of honey and real-world application

Application of lyophilized plum pomace as a functional ingredient in a plum spread: Optimizing texture, colour and phenol antioxidants by ANN modelling

(2020) Aleksandra Bajić et al.   LWT-FOOD SCIENCE AND TECHNOLOGY

Detection of durum wheat pasta adulteration with common wheat by infrared spectroscopy and chemometrics: A case study

(2020) Annalisa De Girolamo et al.   LWT-FOOD SCIENCE AND TECHNOLOGY

Comparison of DMA-80 and ICP-MS Combined with Closed-Vessel Microwave Digestion for the Determination of Mercury in Coal

(2020) Siyu Zhang et al.   Journal of Analytical Methods in Chemistry

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

(2019) Xiaolei Zhang et al.   ANALYTICA CHIMICA ACTA

FPGA-Based Hybrid-Type Implementation of Quantized Neural Networks for Remote Sensing Applications

(2019) Xin Wei et al.   SENSORS

End‐to‐end quantitative analysis modeling of near‐infrared spectroscopy based on convolutional neural network

(2019) Yuan‐Yuan Chen et al.   JOURNAL OF CHEMOMETRICS

Feature selection based convolutional neural network pruning and its application in calibration modeling for NIR spectroscopy

(2019) Yuan-yuan Chen et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

IR spectroscopy and chemometrics for physical property prediction of structured lipids produced by interesterification of beef tallow

(2019) A. Burcu Aktas et al.   LWT-FOOD SCIENCE AND TECHNOLOGY

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

FT-IR and Raman spectroscopy data fusion with chemometrics for simultaneous determination of chemical quality indices of edible oils during thermal oxidation

(2019) Huan Liu et al.   LWT-FOOD SCIENCE AND TECHNOLOGY

Combining convolutional neural networks and on-line Raman spectroscopy for monitoring the Cornu Caprae Hircus hydrolysis process

(2019) Xu Yan et al.   SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY

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

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

A simple approach for rapid detection and quantification of adulterants in stingless bees ( Heterotrigona itama ) honey

(2018) Kuan Wei Se et al.   FOOD RESEARCH INTERNATIONAL

Convolutional neural network-based multimodal image fusion via similarity learning in the shearlet domain

(2018) Haithem Hermessi et al.   NEURAL COMPUTING & APPLICATIONS

Chemometric classification and quantification of cold pressed grape seed oil in blends with refined soybean oils using attenuated total reflectance–mid infrared (ATR–MIR) spectroscopy

(2018) Gönül Akin et al.   LWT-FOOD SCIENCE AND TECHNOLOGY

NIRS feature extraction based on deep auto-encoder neural network

(2017) Ting Liu et al.   INFRARED PHYSICS & TECHNOLOGY

Recent advancements in detecting sugar-based adulterants in honey – A challenge

(2017) Liming Wu et al.   TRAC-TRENDS IN ANALYTICAL CHEMISTRY

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

(2016) Hoo-Chang Shin et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Deep Learning in Drug Discovery

(2015) Erik Gawehn et al.   Molecular Informatics

Deep learning

(2015) Yann LeCun et al.   NATURE

Analysis of adulteration in honey with standard sugar solutions and syrups using attenuated total reflectance-Fourier transform infrared spectroscopy and multivariate methods

(2012) M.A. Rios-Corripio et al.   CyTA-Journal of Food

Rapid detecting total acid content and classifying different types of vinegar based on near infrared spectroscopy and least-squares support vector machine

(2012) Shi Ji-yong et al.   FOOD CHEMISTRY

A feasibility study on on-line determination of rice wine composition by Vis–NIR spectroscopy and least-squares support vector machines

(2008) H.Y. Yu et al.   FOOD CHEMISTRY