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Use DCNN to classify the electronic nose data set, and try to use SDA for drift compensation.

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PieceZhang/dcnngas-classification-python

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DCNNGasClassification-Python

DCNN分类电子鼻数据集,并尝试使用SDA进行漂移补偿(效果不好)

Ref:

  1. An optimized Deep Convolutional Neural Network for dendrobium classification based on electronic nose

  2. Gas Classification Using Deep Convolutional Neural Networks

  3. Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach

  4. ArcFace:Additive Angular Margin Loss for Deep Face Recognition

Datasets:

  1. 10 boards, Ref: Chmical gas sensor drift compensation using calssifier ensembles
  2. 5 boards, Ref: Calibration transfer and drift counteraction in chemical sensor arrays using Direct Standardization

错误(已修改):

在network2中,BN层之前的conv层不应使用激活函数。ReLU激活函数应放置在BN层之后。(并未明显影响精度)

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Use DCNN to classify the electronic nose data set, and try to use SDA for drift compensation.

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