A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network

<p dir="ltr">Fast recognition of flammable and toxic gas species within very short response time is a challenging task for the gas sensing devices adopted in a wide range of applications. The recognition accuracies of the previous implementations are always constrained by the limited...

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Bibliographic Details
Main Author:	Xiaofang Pan (1895950) (author)
Other Authors:	Haien Zhang (19653919) (author), Wenbin Ye (63056) (author), Amine Bermak (1895947) (author), Xiaojin Zhao (9034805) (author)
Published:	2019
Subjects:	Information and computing sciences Artificial intelligence Data management and data science Feature extraction Computer architecture Microprocessors Convolutional codes Recurrent neural networks Data mining Sensors Electronic nose fast gas recognition long short-term memory drift counteraction
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A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network

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