Research on food safety sampling inspection system based on deep learning

With numerous promising cases in image processing, voice recognition, target detection, and other fields, deep learning (DL) have proven to be an advanced tool for big data analysis. It's been used food science engineering recently as well. This is the first food-related study that we are aware of. We gave a brief overview of DL this paper, well comprehensive descriptions structure some common neural network (DNN) architectures training approaches. looked at hundreds publications processing method address problems issues domain, such identification, calorie estimating, fruit, potato, meat, aquatic commodity quality supply chain, pollution. Each particular challenges, datasets, preprocessing techniques, networks systems used, efficiency achieved, comparisons with solutions. examined degree which being safety domain found positive developments article. According our results, outperforms approaches manual attribute extractors, traditional machine algorithms, technique inspection.