Estimating the composition of food nutrients from hyperspectral signals based on deep neural networks

HIGHLIGHTS

  • who: DaeHan Ahn and colleagues from the Department of Robotics Engineering, Hanyang University, Hanyang daehak-ro, Ansan, Korea have published the Article: Estimating the Composition of Food Nutrients from Hyperspectral Signals Based on Deep Neural Networks, in the Journal: (JOURNAL)
  • what: To meet this need the authors propose a new approach learning that precisely estimates the composition of carbohydrates proteins and fats from of foods obtained by using low-cost spectrometers. Specifically the authors develop a system consisting of multiple neural networks for estimating food nutrients followed by detecting and discarding estimation anomalies. Motivated by . . .

     

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