Abnormal area identification of corn ear based on semi‐supervised learning-Reference-Cited by-同舟云学术

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Abnormal area identification of corn ear based on semi‐supervised learning

Published:2022-04-14 Issue:9 Volume:16 Page:2351-2360
ISSN:1751-9659
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Wei Jian¹,Ma Qin¹²,Wang Weitao¹,Guo Hao³,Liu Zhe³,Zhang Jiajing⁴⁵

Affiliation:

1. College of Information and Electrical Engineering China Agricultural University Beijing China

2. Key Laboratory of Agricultural Machinery Monitoring and Big Data Application Ministry of Agriculture and Rural Affairs Beijing China

3. College of Land Science and Technology China Agricultural University Beijing China

4. The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

5. School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/ipr2.12492

Reference31 articles.

1. Deep learning in agriculture: A survey

2. A review of computer vision technologies for plant phenotyping

3. Automatic inspection machine for maize kernels based on deep convolutional neural networks

4. High-throughput corn ear screening method based on two-pathway convolutional neural network

5. Shi B. Zhou X. Qin Z. et al.:Corn ear quality recognition based on DCGAN data enhancement and transfer learning. In:4th International Conference on Electronics Communications and Control Engineering pp.62–68. (2021)

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