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Food Safety

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Food Image Recognition and Food Safety Detection Method Based on Deep Learning.

Computational intelligence and neuroscience
With the development of machine learning, as a branch of machine learning, deep learning has been applied in many fields such as image recognition, image segmentation, video segmentation, and so on. In recent years, deep learning has also been gradua...

Trace Identification and Visualization of Multiple Benzimidazole Pesticide Residues on Leaves Using Terahertz Imaging Combined with Deep Learning.

International journal of molecular sciences
Molecular spectroscopy has been widely used to identify pesticides. The main limitation of this approach is the difficulty of identifying pesticides with similar molecular structures. When these pesticide residues are in trace and mixed states in pla...

Recent advancement in nano-optical strategies for detection of pathogenic bacteria and their metabolites in food safety.

Critical reviews in food science and nutrition
Pathogenic bacteria and their metabolites are the leading risk factor in food safety and are one of the major threats to human health because of the capability of triggering diseases with high morbidity and mortality. Nano-optical sensors for bacteri...

Accurate classification of Listeria species by MALDI-TOF mass spectrometry incorporating denoising autoencoder and machine learning.

Journal of microbiological methods
Listeria monocytogenes belongs to the category of facultative anaerobic bacteria, and is the pathogen of listeriosis, potentially lethal disease for humans. There are many similarities between L. monocytogenes and other non-pathogenic Listeria specie...

Application of machine learning to the monitoring and prediction of food safety: A review.

Comprehensive reviews in food science and food safety
Machine learning (ML) has proven to be a useful technology for data analysis and modeling in a wide variety of domains, including food science and engineering. The use of ML models for the monitoring and prediction of food safety is growing in recent...

Evaluation of Tourism Food Safety and Quality with Neural Networks.

Computational intelligence and neuroscience
Food safety issues are inextricably linked to people's lives and, in extreme cases, endanger public safety and social stability. People are becoming increasingly concerned about food safety issues in a modern society with high-quality economic develo...

An Entity Relationship Extraction Model Based on BERT-BLSTM-CRF for Food Safety Domain.

Computational intelligence and neuroscience
Dealing with food safety issues in time through online public opinion incidents can reduce the impact of incidents and protect human health effectively. Therefore, by the smart technology of extracting the entity relationship of public opinion events...

An Entity Relation Extraction Method for Few-Shot Learning on the Food Health and Safety Domain.

Computational intelligence and neuroscience
In recent years, entity relation extraction has been a critical technique to help people analyze complex structured text data. However, there is no advanced research in food health and safety to help people analyze the complex concepts between food a...

Combining deep learning and fluorescence imaging to automatically identify fecal contamination on meat carcasses.

Scientific reports
Food safety and foodborne diseases are significant global public health concerns. Meat and poultry carcasses can be contaminated by pathogens like E. coli and salmonella, by contact with animal fecal matter and ingesta during slaughter and processing...

Toward in-process technology-aided automation for enhanced microbial food safety and quality assurance in milk and beverages processing.

Critical reviews in food science and nutrition
Ensuring the safety of food products is critical to food production and processing. In food processing and production, several standard guidelines are implemented to achieve acceptable food quality and safety. This notwithstanding, due to human limit...