Deep-Learning-Based Defective Bean Inspection with GAN-Structured Automated Labeled Data Augmentation in Coffee Industry

Deep-Learning-Based Defective Bean Inspection with GAN-Structured Automated Labeled Data Augmentation in Coffee Industry

In the production process from green beans to coffee bean packages, the defective bean removal (or in short, defect removal) is one of most labor-consuming stages, and many companies investigate the automation of this stage for minimizing human efforts. In this paper, we propose a deep-learning-base...

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Bibliographic Details
Main Authors: Yung-Chien Chou, Cheng-Ju Kuo, Tzu-Ting Chen, Gwo-Jiun Horng, Mao-Yuan Pai, Mu-En Wu, Yu-Chuan Lin, Min-Hsiung Hung, Wei-Tsung Su, Yi-Chung Chen, Ding-Chau Wang, Chao-Chun Chen
Format: Article
Language:English
Published: MDPI AG 2019-10-01
Series:Applied Sciences
Subjects:
automatic defect inspection
machine learning
smart agriculture
automation engineering
data augmentation
applied artificial intelligence
gan optimizer
Online Access:https://www.mdpi.com/2076-3417/9/19/4166

Internet

https://www.mdpi.com/2076-3417/9/19/4166

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