The detection of saffron adulterants using a deep neural network approach based on RGB images taken under uncontrolled conditions

作者：

Highlights：

• Saffron adulterants detected and classified using a deep learning algorithm.

• RGB photos took under uncontrolled/unstructured conditions.

• Five CNN models were proposed for classification.

• The best-proposed model can process an image in 36.26 ms with 99.67% accuracy.

摘要

•Saffron adulterants detected and classified using a deep learning algorithm.•RGB photos took under uncontrolled/unstructured conditions.•Five CNN models were proposed for classification.•The best-proposed model can process an image in 36.26 ms with 99.67% accuracy.

论文关键词：Saffron,Adulterants detection,Deep neural network

论文评审过程：Received 22 October 2021, Revised 10 March 2022, Accepted 11 March 2022, Available online 14 March 2022, Version of Record 15 March 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116890