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

A review on meat quality evaluation methods based on non-destructive computer vision and artificial intelligence technologies

(2021) Yinyan Shi et al.   Food Science of Animal Resources

The review of food safety inspection system based on artificial intelligence, image processing, and robotic

(2021) Tzu-Chia CHEN et al.   Food Science and Technology

Handheld Multispectral Fluorescence Imaging System to Detect and Disinfect Surface Contamination

(2021) Mitchell Sueker et al.   SENSORS

A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects

(2021) Zewen Li et al.   IEEE Transactions on Neural Networks and Learning Systems

Application of Deep Learning in Food: A Review

(2019) Lei Zhou et al.   COMPREHENSIVE REVIEWS IN FOOD SCIENCE AND FOOD SAFETY

Multispectral Fluorescence Imaging Technique for On-Line Inspection of Fecal Residues on Poultry Carcasses

(2019) Youngwook Seo et al.   SENSORS

Hyperspectral Determination of Fluorescence Wavebands for Multispectral Imaging Detection of Multiple Animal Fecal Species Contaminations on Romaine Lettuce

(2018) Hyunjeong Cho et al.   Food and Bioprocess Technology

Food safety in the 21st century

(2018) Fred Fung et al.   Biomedical Journal

An Economic Evaluation of PulseNet

(2016) Robert L. Scharff et al.   AMERICAN JOURNAL OF PREVENTIVE MEDICINE

Evaluation of the quality of cold meats by computer-assisted image analysis

(2016) Piotr Zapotoczny et al.   LWT-FOOD SCIENCE AND TECHNOLOGY

Economic Burden from Health Losses Due to Foodborne Illness in the United States

(2011) Robert L. Scharff   JOURNAL OF FOOD PROTECTION

Line-scan hyperspectral imaging for real-time in-line poultry fecal detection

(2011) Bosoon Park et al.   Journal of Food Measurement and Characterization