  Fruit recognition using Deep Convolutional Neural Network (CNN) is one of the
most promising applications in computer vision. In recent times, deep learning
based classifications are making it possible to recognize fruits from images.
However, fruit recognition is still a problem for the stacked fruits on
weighing scale because of the complexity and similarity. In this paper, a fruit
recognition system using CNN is proposed. The proposed method uses deep
learning techniques for the classification. We have used Fruits-360 dataset for
the evaluation purpose. From the dataset, we have established a dataset which
contains 17,823 images from 25 different categories. The images are divided
into training and test dataset. Moreover, for the classification accuracies, we
have used various combinations of hidden layer and epochs for different cases
and made a comparison between them. The overall performance losses of the
network for different cases also observed. Finally, we have achieved the best
test accuracy of 100% and a training accuracy of 99.79%.
