A Real-Time Junk Food Recognition System Based on Machine Learning

As a result of bad eating habits, humanity may be destroyed. People are constantly on the lookout for tasty foods, with junk foods being most common source. consequence, our patterns shifting, and we’re gravitating toward food more than ever, which is health increases risk acquiring problems. Machine learning principles applied in every aspect lives, one them object recognition via image processing. However, because vary nature, this procedure crucial, traditional methods like ANN, SVM, KNN, PLS etc., will low accuracy rate. All these issues were defeated by Deep Neural Network. In work, we created fresh dataset 10,000 data points from 20 classifications to try recognize foods. set was gathered using Google search engine, thought one-of-a-kind way. The goal achieved Convolution Network (CNN) technology, well-known We 98.05% rate throughout research, satisfactory. addition, conducted test based real-life event, outcome extraordinary. Our advance research next level, so that it future study. ultimate create system would encourage people avoid health-conscious.