A surface defect detection system for golden diamond pineapple based on CycleGAN and YOLOv4

Author:

Chen Ssu-Han,Lai Yu-Wei,Kuo Chung-Lun,Lo Chieh-Yi,Lin Yu-Sung,Lin Yan-Rung,Kang Chih-Hsiang,Tsai Chia-Chun

Funder

Ministry of Science and Technology, Taiwan

Publisher

Elsevier BV

Subject

General Computer Science

Reference31 articles.

1. Ripeness level classification for pineapple using RGB and HSI colour maps;Abu Bakar;J. Theor. Appl. Inf. Technol.,2013

2. Assessing the State of Maturation of the Pineapple in Its Perolera Variety Using Computer Vision Techniques;Angel,2015

3. Bochkovskiy, A., Wang, C. Y., Liao, H.Y.M., 2020. Yolov4: Optimal speed and accuracy of object detection. arXiv preprint arXiv:2004.10934.

4. Leafgan: An effective data augmentation method for practical plant disease diagnosis;Cap,2020

5. Detecting and measuring defects in wafer die using gan and yolov3;Chen;Appl. Sci.,2020

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