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Deep Learning Based Classification System for Recognizing Local Spinach

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dc.contributor.author Islam, Mirajul
dc.contributor.author Ria, Nushrat Jahan
dc.contributor.author Ani, Jannatul Ferdous
dc.contributor.author Masum, Abu Kaisar Mohammad
dc.contributor.author Abujar, Sheikh
dc.contributor.author Hossain, Syed Akhter
dc.date.accessioned 2024-03-31T06:27:03Z
dc.date.available 2024-03-31T06:27:03Z
dc.date.issued 2022-01-03
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/11933
dc.description.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%. en_US
dc.language.iso en_US en_US
dc.publisher Springer en_US
dc.subject Deep learning en_US
dc.subject Neural networks en_US
dc.subject Classification systems en_US
dc.title Deep Learning Based Classification System for Recognizing Local Spinach en_US
dc.type Article en_US


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