Automated Detection of Coffee Bean Defects using Multi-Deep Learning Models
Author:
Affiliation:
1. University of Dong Hwa,Department of Electrical Engineering,Hualien,Taiwan
Funder
Ministry of Science and Technology
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10233953/10233955/10234059.pdf?arnumber=10234059
Reference10 articles.
1. Densely Connected Convolutional Networks
2. Deep Convolutional Neural Network for Coffee Bean Inspection
3. EfficientNetV2: smaller models and faster training;tan;38th International Conference on Machine Learning,2021
4. Grading and Profiling of Coffee Beans for International Standards Using Integrated Image Processing Algorithms and Back-Propagation Neural Network
5. Real-Time Classification of Green Coffee Beans by Using a Convolutional Neural Network
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1. Enhancing coffee bean classification: a comparative analysis of pre-trained deep learning models;Neural Computing and Applications;2024-04-01
2. A Remote Access Server with Chatbot User Interface for Coffee Grinder Burr Wear Level Assessment Based on Imaging Granule Analysis and Deep Learning Techniques;Applied Sciences;2024-02-05
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