Analysing Gas Data using Deep Learning and 2D Gramian Angular Fields
The used dataset is available publically at the UCI repository for the experiments. In this work Dynamic mixture of gases, the dataset is used for the classification, where this time series dataset is converted to 2D GAF representation and then classify by using the ALexNet classifier. Further, the 1D time series dataset is classified by using deep learning architecture named GasNEt0CNN.
Email Address of Submitting Authormuhammadjaleel88@gmail.com
Submitting Author's InstitutionDe Montfort University Leicester
Submitting Author's Country
- United Kingdom