Android-Based Rice Variety Classifier (Arvac) Using Convolutional Neural Network

— Rice is the world’s most important cereal. It constitutes the world’s guideline source of nourishment, being the essential grain for the planet’s most significant populace. It is the staple nourishment and source of dietary vitality and protein. Within the current grain-handling frameworks, grain sort and quality are evaluated by mere visual review. This assessment handle is, be that as it may, dull and time-consuming. Decision-making capabilities can be genuinely influenced by a physical condition such as weakness in vision, the current mental state caused by predispositions and work weight, and working condition such as a disgraceful lighting condition. In this paper, an Android-based image recognition system using Convolutional Neural Network was used as a new method to classify and identify rice variety in terms of visual features such as size, color, shape, and texture of the seeds. Fifty (50) rice samples having eleven (11) rice varieties were used in the study for testing. Results in the study show an overall accuracy rate of 93.8%. Such high accuracy rate confirms that the Android-based Rice Variety Classifier can be used as a tool for classifying rice grains.