Abstract
Food safety has been a major concern in recent years as a result of numerous food safety events in many nations. This could increase the health risks associated with eating low-quality food, lowering customer confidence in food safety. It is critical to overcome this challenge and gain consumer trust in order to improve food quality and safety. To address this issue, we suggested an intelligent deep learning method for identifying which foods are potentially harmful to human health based on chemical and additive qualities, which could have a significant impact on consumer health. The findings of our survey show that deep learning surpasses other methods such as manual feature extractors, as well as the promising findings of categorization of hazardous food, further research efforts to apply deep learning to the field of food will be made in the future.
Highlights
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Summary
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