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Application of electronic nose to beer recognition using supervised artificial neural networks.

, , , and . CoDIT, page 640-645. IEEE, (2014)

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Support Vector Machine Regression for Calibration Transfer between Electronic Noses Dedicated to Air Pollution Monitoring., , , and . Sensors, 18 (11): 3716 (2018)Reduction of drift impact in gas sensor response to improve quantitative odor analysis., , , and . ICIT, page 928-933. IEEE, (2017)A comparison between SVM and PLS for E-nose based gas concentration monitoring., , , , and . ICIT, page 1335-1339. IEEE, (2018)Orthogonal Signal Correction to Improve Stability Regression Model in Gas Sensor Systems., , , and . J. Sensors, (2017)Optimization of an electronic nose for rapid quantitative recognition., , , and . CoDIT, page 736-741. IEEE, (2014)Sensors and Features Selection for Robust Gas Concentration Evaluation., , , and . SENSORNETS, page 237-243. SciTePress, (2014)Field Evaluation of Low Cost Sensors Array for Air Pollution Monitoring., , , and . IDAACS, page 849-853. IEEE, (2019)Empiric Unsupervised Drifts Correction Method of Electrochemical Sensors for in Field Nitrogen Dioxide Monitoring., , , and . Sensors, 21 (11): 3581 (2021)Application of electronic nose to beer recognition using supervised artificial neural networks., , , and . CoDIT, page 640-645. IEEE, (2014)Calibration Transfer to Address the Long Term Drift of Gas Sensors for in Field NO2 Monitoring., , , and . ICCAD, page 1-6. IEEE, (2021)