Rice grains and grain impurity segmentation method based on a deep learning algorithm-NAM-EfficientNetv2

Author:

Liu Qinghua,Liu Weikang,Liu Yishan,Zhe Tiantian,Ding Bochuan,Liang Zhenwei

Publisher

Elsevier BV

Subject

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

Reference28 articles.

1. Improved digital image-based assessment of soil aggregate size by applying convolutional neural networks;Alirezazadeh;Comput. Electron. Agri.,2021

2. Online recognition method of impurities and broken paddy grains based on machine vision;Chen;Trans. Chin. Soc. Agri. Eng.,2018

3. Segmentation of impurity rice grain images based on U-Net model;Chen;Trans. Chin. Soc. Agri. Eng. (Trans. CSAE),2020

4. Real-time grain impurity sensing for rice combine harvesters using image processing and decision-tree algorithm;Chen;Comput. Electron. Agric.,2020

5. SeNet: structured edge network for seal and segmentation;Cheng;IEEE Geosci. Remote Sens. Lett.,2016

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