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Deep Learning Based Classification System for Recognizing Local Spinach
Mirajul Islam, Jannatul Ferdous Ani, Abu Kaisar Mohammad Masum, Nushrat Jahan Ria, Sheikh Abujar, Syed Akhter Hossain,

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%.

Spinach recognition, Convolutional neural network (CNN), Deep learning, Image classification, Evaluation metric
Journal or Conference Name
Lecture Notes in Networks and Systems
Publication Year