A Novel Gas Recognition Algorithm for Gas Sensor Array Combining Savitzky–Golay Smooth and Image Conversion Route
نویسندگان
چکیده
In recent years, the application of Deep Neural Networks to gas recognition has been developing. The classification performance Network depends on efficient representation input data samples. Therefore, a variety filtering methods are firstly adopted smooth filter sensing response data, which can remove redundant information and greatly improve classifier. Additionally, optimization experiment Savitzky–Golay algorithm is carried out. After that, we used Gramian Angular Summation Field (GASF) method encode into two-dimensional images. addition, augmentation technology reduce impact small sample numbers classifier robustness generalization ability model. Then, combined with fine-tuning GoogLeNet neural network, owns automatically learn characteristics deep samples, four gases finally realized: methane, ethanol, ethylene, carbon monoxide. Through setting different comparison experiments, it known that pretreatment effectively improves accuracy classifier, network superior fine-tuned ResNet50, Alex-Net, ResNet34 networks in both processing times. Finally, highest results our proposed route 99.9%, better than other similar work.
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ژورنال
عنوان ژورنال: Chemosensors
سال: 2023
ISSN: ['2227-9040']
DOI: https://doi.org/10.3390/chemosensors11020096