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Deep Neural Networks for Image-Based Dietary Assessment
Published on: March 13, 2021
Artificial neural networks in foodstuff analyses: Trends and perspectives A review
1Dipartimento di Chimica - Sapienza Università di Roma, P.le Aldo Moro 5, I-00185 Rome, Italy. fmmonet@homail.com
Analytica Chimica Acta
|February 17, 2009
Abstract:
Artificial neural networks are a family of non-linear computational methods, loosely inspired by the human brain, that have found application in an increasing number of fields of analytical chemistry and specifically of food control. In this review, the main neural network architectures are described and examples of their application to solve food analytical problems are presented, together with some considerations about their uses and misuses.
