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Deep Learning Based Classification System for Recognizing Local Spinach

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Advances in Deep Learning, Artificial Intelligence and Robotics

Abstract

A deep learning model gives an incredible result for image processing by studying from the trained dataset. Spinach is a leaf vegetable that contains vitamins and nutrients. In our research, a Deep learning method has been used that can automatically identify spinach and this method has a dataset of a total of five species of spinach that contains 3785 images. Four Convolutional Neural Network (CNN) models were used to classify our spinach. These models give more accurate results for image classification. Before applying these models there is some preprocessing of the image data. For the preprocessing of data, some methods need to happen. Those are RGB conversion, filtering, resize and rescaling, and categorization. After applying these methods image data are preprocessed and ready to be used in the classifier algorithms. The accuracy of these classifiers is in between 98.68 and 99.79%. Among those models, VGG16 achieved the highest accuracy of 99.79%.

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Acknowledgements

We gratefully acknowledge for providing GPU support from Computational Intelligence Lab for providing the necessary support. We thank, Dept. of CSE, Daffodil International University. Moreover, thanks to the anonymous reviewers for their valuable comments and feedback.

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Correspondence to Mirajul Islam .

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Islam, M., Ria, N.J., Ani, J.F., Masum, A.K.M., Abujar, S., Hossain, S.A. (2022). Deep Learning Based Classification System for Recognizing Local Spinach. In: Troiano, L., et al. Advances in Deep Learning, Artificial Intelligence and Robotics. Lecture Notes in Networks and Systems, vol 249. Springer, Cham. https://doi.org/10.1007/978-3-030-85365-5_1

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