Authors : A. Antonidoss, S. Lakshmoji, S. Ramoji and K. Sumith
Abstract: Fruits are the major source of food for humans. According to the scientific research done it is found out that quality seeds are needed which in turn leads to the requirement of quality fruits for better yield of new crops. So, it is required for farmers to identify the correct stage of fruit. Farmers spend their lives solely to utilize their time to discover this extraordinary aspect of farming. Instead of farmers using their time in this process they can use their effort in the fields where their work cannot be replaced by any of the technological advancements and this process can be automated by the latest technologies. With the advancement of technology, the process of identifying the stages of fruits can be done in short span of time by using techniques like object detection which has gained a huge popularity in recent times. It mainly involves two phases. The first phase is to identify the type of the given fruit and the second phase is to classify the stage of the fruit which tells how likely the given fruit is suitable for planting. The first phase can be obtained by using Faster R-CNN of YOLO object detection model which is faster than R-CNN. The second phase can be obtained by using SVM model.
A. Antonidoss, S. Lakshmoji, S. Ramoji and K. Sumith, 2021. Fruit Stage Classification using Machine Learning. Asian Journal of Information Technology, 20: 130-133.