Recognizing Fresh and Rotten Fruits Using Deep Learning Techniques

Abstract

Agriculture 4.0 aims at automation in all parts of supply chain of agriculture. In precision agriculture, precise execution of any task is done by using machine learning techniques. These techniques work on historical information. In horticulture, efficient technique for automated identification of fresh and rotten fruits is required. Automated fruit recognition will help farmers, traders, and customers with quality grading. It will help to reduce efforts and improve accuracy in fruit sorting. The time required for sorting fruits will be reduced which in turn will reduce total supply chain time. Customers will get more fresh fruits, and all stakeholders will be benefited. Automating fruit classification is the need of time for exporting good quality fruits. In this line, this chapter explains about classification of fruits using deep learning techniques. Deep learning is a kind of machine learning, based on artificial neural networks. Artificial neural network technique is inspired from working of human brain neurons. Convolution neural networks have inevitable capability of classifying images in required number of categories. It works on number of features and gives good results for classification task. This chapter shows how deep learning does fruit recognition for two categories as fresh fruit and rotten fruit.