Markov Transition Field Combined with Convolutional Neural Network Improved the Predictive Performance of Near-Infrared Spectroscopy Models for Determination of Aflatoxin B1in Maize

HIGHLIGHTS

• who: Bo Wang and colleagues from the School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, China have published the research work: Markov Transition Field Combined with Convolutional Neural Network Improved the Predictive Performance of Near-Infrared Spectroscopy Models for Determination of Aflatoxin B1in Maize, in the Journal: Foods 2022, 11, 2210. of 25/07/2022
• what: This work provides a novel approach to monitor the aflatoxin B1 (AFB1 ) content in maize by near-infrared (NIR) spectra-based deep learning models that integrates (MTF) image coding and a convolutional neural network (CNN) strategy. This study . . .
  

   

  

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