As deep learning techniques are increasingly applied with greater depth and sophistication in the food industry,the realm of food image processing has progressively emerged as a central focus of research *** work prov...
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As deep learning techniques are increasingly applied with greater depth and sophistication in the food industry,the realm of food image processing has progressively emerged as a central focus of research *** work provides an overview of key practices in food image processing techniques,detailing common processing tasks including classification,recognition,detection,segmentation,and image retrieval,as well as outlining metrics for evaluating task performance and thoroughly examining existing food image datasets,along with specialized food-related *** terms of methodology,this work offers insight into the evolution of food image processing,tracing its development from traditional methods extracting low and intermediate-level features to advanced deep learning techniques for high-level feature extraction,along with some synergistic fusion of these *** is believed that these methods will play a significant role in practical application scenarios such as self-checkout systems,dietary health management,intelligent food service,disease etiology tracing,chronic disease management,and food safety ***,due to the complex content and various types of distortions in food images,further improvements in related methods are needed to meet the requirements of practical applications in the *** is believed that this study can help researchers to further understand the research in the field of food imaging and provide some contribution to the advancement of research in this field.
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