Intelligent food processing: Journey from artificial neural network to deep learning

Janmenjoy Nayak, Kanithi Vakula, Paidi Dinesh, Bighnaraj Naik, Danilo Pelusi

Abstract: Since its initiation, ANN became popular and also plays a key role in enhancing the latest technology. With an increase in industrial automation and the Internet of Things, now it is easier than ever to collect data and monitor food drying, extrusion, and sterilization, etc. In this industrial revolution, the uses of ANN are found successful in food processing tasks like food grading, safety, and quality check, etc. In recent years, attention on shallow learning approach (i.e. use of earlier developed ANNs) in food processing is escalating as researchers found it extensive exploitation in resolving a lot of complex real-world problems in food processing. In this row, deep learning techniques have not left any stone unturned in the context of intelligent food processing paradigm. In this paper, a detailed analysis has been reported on the advancements of food processing using ANNs, which include the details journey from shallow learning to deep learning in the applications space. Such fusion of technology with the forefront of machine learning, deep learning, and image processing for food processing, is not just the mixture of hybrid concepts, rather it provides a scope to create new dimensions and growth opportunities for each innovation.