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Real-time recognition system of soybean seed full-surface defects based on deep learning

  • Published:2021-08 Issue: Volume:187 Page:106230
  • ISSN:0168-1699
  • Container-title:Computers and Electronics in Agriculture
  • language:en
  • Short-container-title:Computers and Electronics in Agriculture

Author:

Zhao Guoyang,Quan Longzhe,Li Hailong,Feng Huaiqu,Li Songwei,Zhang Shuhan,Liu Ruiqi

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference42 articles.

1. Identification of haploid and diploid maize seeds using convolutional neural networks and a transfer learning approach;Altuntas;Comput. Electron. Agric.,2019

2. Development of a machine for the automatic sorting of pomegranate (Punica granatum) arils based on computer vision;Blasco;J. Food Eng.,2009

3. Identification of paddy varieties based on novel seed angle features;Chaugule;Comput. Electron. Agric.,2016

4. Multiple view image analysis of freefalling U.S. wheat grains for damage assessment;Delwiche;Comput. Electron. Agric.,2013

5. Developer, N., 2020. NVIDIA Jetson nano developer kit. Retrieved from https://developer.nvidia.com/embedded/jetson-nano-developer-kit.

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