Machine Learning AI

In this era, number of Organizations are increasing their businesses using Artificial Intelligence Services to overcome the manual and time consuming tasks for better performance with Quality. So, food Classification and Quality Inspection is also a manual and time consuming task for food Sellers and Pur-chasers Organizations, to address this issue many people propose different systems that can automate such Classification and Inspection process. Automated food classification is a procedure in which foods are classified in several categories in order to generate automated reports about the food categorize. Food Quality Inspection plays critical role in these systems. To automate such Classification and Quality Inspection we propose a system that consist of two main modules, Food Classification and its Quality Checker. For Food classification we design/ trained a model on 30 types of fruit classes including (Acerolas, Apples, Apricots, Avocados, Bananas, Blackberries, Blueberries, Cantaloupes, Cherries, Coconuts, Figs, Grapes Fruits, Grapes, Guava, Kiwifruit, Lemons, Li-mes, Mangos, Olives, Oranges, Passion fruit, Peaches, Pears, Pine Apple, Plums, Pomegranates, Raspber-ries, Strawberries, Tomatoes, Watermelons) with the help of deep convolution neural network (DCNN). The FID30 dataset is used for training and testing of classification model. After classification automated the food quality Inspector module will generate a report based on the fruit class.