# Deep Learning Based Classification System For Recognizing Local Spinach Source: [Deep Learning Based Classification System For Recognizing Local Spinach]() Collection index: [llms.txt]() Data updated: 2025-10-25T23:51:06.318Z Authors: Mirajul Islam, Nushrat Jahan Ria, Jannatul Ferdous Ani, Abu Kaisar Mohammad Masum, Sheikh Abujar, Syed Akhter Hossain Published: 2022-01-06T15:10:41.000Z ## 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%. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. ## Original sources and implementation [Original paper]() [PDF]()