Corpus ID: 208527638

Learning to smell for wellness

@article{Owoeye2019LearningTS,
  title={Learning to smell for wellness},
  author={Kehinde Owoeye},
  journal={ArXiv},
  year={2019},
  volume={abs/1912.00895}
}
Learning to automatically perceive smell is becoming increasingly important with applications in monitoring the quality of food and drinks for healthy living. In todays age of proliferation of internet of things devices, the deployment of electronic nose otherwise known as smell sensors is on the increase for a variety of olfaction applications with the aid of machine learning models. These models are trained to classify food and drink quality into several categories depending on the… Expand

References

SHOWING 1-10 OF 27 REFERENCES
A Novel Semisupervised Deep Learning Method for Human Activity Recognition
  • 17
Electronic Noses and Tongues in Wine Industry
  • 42
  • PDF
Semi-supervised time series classification
  • 253
  • PDF
Domain-Adversarial Training of Neural Networks
  • 3,194
  • PDF
Semi-Supervised Domain Adaptation via Minimax Entropy
  • 118
  • PDF
Activity Recognition Based on Semi-supervised Learning
  • 96
  • PDF
Transfer learning for time series classification
  • 73
  • PDF
Adam: A Method for Stochastic Optimization
  • 63,474
  • PDF
Long Short-Term Memory
  • 38,199
  • PDF
...
1
2
3
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