Advanced Computational Analysis of Artichoke Varieties in India: A Deep Dive into Green Globe, Imperial Star, and Big Heart

The proposed research offers a complete method for grouping different types of artichokes in India. It uses Convolutional Neural Networks (CNN) and Support Vector Machines (SVM). A group of about 12,000 clear pictures was gathered and cleaned up. They included different types of artichokes like Green Globe, Imperial Star, and Big Heart varieties. The dataset was stratified into subsets: 70% for training, 15% for checking, and another 15% for testing. The model is efficient getting 98.31 % accuracy altogether in figuring out the differences between types of artichokes. Measurements like accuracy, find rate and F1-score were calculated. These showed how well the models could correctly classify different kinds of artichokes. The analysis of the confusion matrix found very few mistakes in classifying. This showed that models are strong, but there was some mix-up between types called Imperial Star and Big Heart. This study helps a lot with farming, separating markets, and cooking uses. The models are very helpful for farmers, sellers, and chefs because they improve farming. They meet different preferences of customers with artichokes used in recipes. This study, which gets high correctness, finds ways to make models better. It focuses mostly on reducing mix-ups between very similar types of things. The results show a big improvement in making machines classify different types of artichokes. This is very helpful for those involved and opens up chances for future changes in farming and food businesses alike.