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.

自成立以来，人工神经网络开始流行，并且在增强最新技术方面也发挥着关键作用。随着工业自动化和物联网的发展，现在比以往任何时候都更容易收集数据和监视食品干燥，挤压和灭菌等。在这场工业革命中，人们发现ANN在食品加工等任务中的成功应用近年来，随着研究人员发现浅层学习方法已广泛用于解决食品加工中的许多复杂现实问题，人们对食品加工中浅层学习方法（即使用较早开发的人工神经网络的使用）的关注正逐步增加。食品加工。在这一行中，深度学习技术在智能食品加工范式的背景下丝毫不动摇。在本文中，关于使用人工神经网络的食品加工进展的详细分析报告，包括在应用空间中从浅层学习到深度学习的详细过程。这种技术与机器学习，深度学习和用于食品加工的图像处理技术的最前沿融合在一起，不仅是混合概念的结合，而且还为每个创新创造了新的维度和增长机会。