HCHODetector: Formaldehyde concentration detection based on deep learning. Issue 1 (April 2021) - Cao, Zhihao; Shao, Mingfeng; Shi, Aiju; Qu, Hongchun
Abstract: Currently, deep learning technology is developing rapidly. Deep learning is mainly used in the fields of vision and hearing for human beings, but less in the field of olfactory. Formaldehyde is a common gas harmful to human health. However, the traditional methods of Formaldehyde concentration detection are inefficient in some cases. As for this problem, this paper proposes a novel formaldehyde detector namely HCHODetector. Specifically, this detector is based on deep learning and HSV colour space augmentation. Moreover, we propose a novel Mask-guided module and a novel pre-training network to enhance the colour discrimination ability of HCHODetector. As a consequence, the experimental results show that the detection error is within 0.08 mg/m 3 in the actual environment, which provides a new idea for Formaldehyde concentration detection.