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Deep transfer learning to verify quality and safety of ground coffee

  • Published:2021-04 Issue: Volume:122 Page:107801
  • ISSN:0956-7135
  • Container-title:Food Control
  • language:en
  • Short-container-title:Food Control

Author:

Pradana-López Sandra,Pérez-Calabuig Ana M.,Cancilla John C.,Lozano Miguel Ángel,Rodrigo Carlos,Mena María Luz,Torrecilla José S.

Funder

Universidad Complutense de Madrid

Publisher

Elsevier BV

Subject

Food Science,Biotechnology

Cited by 27 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. SC-HybridSN: A deep learning network method for rapid discriminant analysis of industrial paraffin contamination levels in rice;Journal of Food Composition and Analysis;2024-09

2. The emerging role of biotechnological advances and artificial intelligence in tackling gluten sensitivity;Critical Reviews in Food Science and Nutrition;2024-08-15

3. Identification, Classification, and Grading of Crops Grain Using Computer Intelligence Techniques;Advances in Business Information Systems and Analytics;2024-06-28

4. Enhancing coffee bean classification: a comparative analysis of pre-trained deep learning models;Neural Computing and Applications;2024-04-01

5. From Frisee to Belgian Endive: A Deep Learning and Ensemble Approach to Classifying Endive Varieties in India;2024 11th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO);2024-03-14
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