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Deep Learning Based Classification System For Recognizing Local Spinach

Computer Vision and Pattern Recognition 2022-01-07 v1 Machine Learning Image and Video Processing

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 & rescaling, and categorization. After applying these methods image data are pre-processed and ready to be used in the classifier algorithms. The accuracy of these classifiers is in between 98.68% - 99.79%. Among those models, VGG16 achieved the highest accuracy of 99.79%.

Keywords

Cite

@article{arxiv.2201.02093,
  title  = {Deep Learning Based Classification System For Recognizing Local Spinach},
  author = {Mirajul Islam and Nushrat Jahan Ria and Jannatul Ferdous Ani and Abu Kaisar Mohammad Masum and Sheikh Abujar and Syed Akhter Hossain},
  journal= {arXiv preprint arXiv:2201.02093},
  year   = {2022}
}

Comments

10 pages, 4 figures, supplemental materials. Accepted in 2nd International Conference on Deep Learning, Artificial Intelligence and Robotics,(ICDLAIR) 2020

R2 v1 2026-06-24T08:41:59.601Z