Analysing Gas Data using Deep Learning and 2D Gramian Angular Fields

Autor: Hossein Malekmohamadi
Rok vydání: 2022
Popis: 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.
Databáze: OpenAIRE