Food recognition and feature extraction with artificial intelligence

It is clear that the food and beverage industry will never end and will never get old, as people need nourishment to live. For this reason, the food industry has become a growing sector day by day. With the widespread use of technology, even foods found in different parts of theworld are recognizable to people. Food types have many different features, from the amount of calories, the nutrients contained in it, to the types of processing. Food menus may vary in certain diseases, sports nutrition, healthy life recommendations or different world cuisines. The main factor in choosing this study is to help people who need to make different menu choices in different situations, with artificial intelligence applications. In recent years, great advances have been made in the field of image recognition and classification. Deep learning studies have been carried out in many areas such as image recognition, image segmentation, and video segmentation. Many image recognition and classification methods based on artificial intelligence have been proposed, and these methods have increased the accuracy and efficiency in image detection. Image recognition applications are also applied to food recognition. However, due to the diversity of foods in the food recognition area, the degree of complexity is high, the accuracy and speed of recognition is lower. This study aims to try to solve this problem and develop a neural network-based food image recognition method. In this study, food images automatically identifies the correct food and predicts the food class. New products based on artificial intelligence approaches that present the nutritional values contained to the user a system design is aimed. In the training part of the system, a deep learning model consisting of a convolutional neural network will be created to classify foods into certain categories. The convolutional neural network model has been shown as a powerful technique of deep learning in recent years. With the recognition of food through photography, it is aimed to be a basis for many applications that can be developed in the future.