A Machine-Learning Based Microwave Sensing Approach to Food Contaminant Detection
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9179985/9180369/09181293.pdf?arnumber=9181293
Cited by 7 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. Near field food contamination detection technique employing a compact Antipodal Vivaldi antenna;AEU - International Journal of Electronics and Communications;2024-10
2. Emerging non-invasive microwave and millimeter-wave imaging technologies for food inspection;Critical Reviews in Food Science and Nutrition;2024-07
3. Machine learning algorithm to extract properties of ATE phantoms from microwave measurements;International Journal of Microwave and Wireless Technologies;2024-02-08
4. Enhanced Machine-Learning Flow for Microwave-Sensing Systems to Detect Contaminants in Food;2023 IEEE Conference on AgriFood Electronics (CAFE);2023-09-25
5. Development of a Deep-Learning Pipeline to Detect and Locate Contaminants of Industrial Products via non-Invasive Microwave Signals;2023 IEEE Conference on AgriFood Electronics (CAFE);2023-09-25
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