Fruit Detection Using Convolution Neural Network


  • Prashant Kumar, Tamal Datta, Sujata Chakravarty


Fruit classification has emerged as a research area in the recent past. An algorithm based on convolution neural network (CNN) has been applied for fruit detection in this article. We have used high-quality, fruit-containing image dataset for training a neural network to detect fruits. The image regions are retrieved using a selective search algorithm. Computer vision is one of the most popular technologies in this era of innovation. The experimental results show that deep neural networks provide more accurate results compared with other machine learning algorithms. In this paper we briefly discuss the usage of deep learning algorithms and also CNN. This model works efficiently with this architecture for fruit recognition. And also we use various hidden layer combinations and epochs for different cases and compare them.




How to Cite

Prashant Kumar, Tamal Datta, Sujata Chakravarty. (2020). Fruit Detection Using Convolution Neural Network. International Journal of Modern Agriculture, 9(3), 1069 - 1075. Retrieved from