Correlation-Based Incremental Learning Network for Gas Sensors Drift Compensation Classification
Author:
Publisher
ASTES Journal
Subject
Management of Technology and Innovation,Physics and Astronomy (miscellaneous),Engineering (miscellaneous)
Link
https://www.astesj.com/publications/ASTESJ_050479.pdf
Reference18 articles.
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3. L. Pan, W. Zhang, N. Zhu, S. Mao, K. Tu, "Early detection and classification of pathogenic fungal disease in post-harvest strawberry fruit by electronic nose and gas chromatography-mass spectrometry" Food Research International, 62, 162-168, 2014. http://dx.doi.org/10.1016/j.foodres.2014.02.020
4. B. Tudu, A. Jana, A. Metla, D. Glosh, N. Bhattacharyya, "Electronic nose for black tea quality evaluation by an incremental RBF network" Sensors and Actuators B: Chemical, 138(1), 90-95, 2009. http://dx.doi.org/10.1016/j.snb.2009.02.025
5. Y. Yang, H. Liu, Y. Gu, "A Model Transfer Learning Framework With Back-Propagation Neural Network for Wine and Chinese Liquor Detection by Electronic Nose" IEEE Access, 8, 105278-105285, 2020. https//doi.org/10.1109/ACCESS.2020.2999591
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