Wine classification by taste sensors made from ultra-thin films and using neural networks

By A. Riul, H. C. D. Sousa, Roger R. Malmegrim, D. Santos, A. C. P. L. F. D. Carvalho, F. Fonseca, O. Oliveira, Luiz H. C. Mattoso. 2004

168 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Nutrition and Dietetics, Sensory Systems

View Paper: https://www.semanticscholar.org/paper/40e34602c232aacd72bbef14a9f1a278f8e3482a

How researchers see this paper

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1. S. S. Bari
2. A. Ganguli
3. P. Kapur
4. Anupma Sharma
5. Madan Lal Singla
6. Amol P. Bhondekar
7. R. Vig
8. Arindam Bhakta

Citations in the corpus

• Performance Evaluation of a Novel iTongue for Indian Black Tea Discrimination (2010, background): “In comparison with potentiometry and especially with voltammetry, the impedance measurements are advantageous because of the potential experimental simplicity and the reduction of the response times [9].”