Deep Learning-Based Fruits And Vegetables Recognition Using Convolutional Neural Network

In this study, a system is developed to improve the methods and processes of identifying fruits and vegetable by both farmers and a normal human, this research tends to provide an approach for identification or classification of fruits and vegetables through a deep learning method that is known as Convolutional Neural Networks (CNNs) in more reliable and faster way. The CNN architecture is used to train a model for different features of an image that is provided in the dataset and hence classify what fruit or vegetable it is. This model is trained on a dataset, containing various images of 36 different fruits and vegetables. This model showcases an accuracy rate of 95.15%.