Intelligent Grading of Tobacco Leaves Using an Improved Bilinear Convolutional Neural Network

At present, tobacco leaf grading relies mainly on manual classification, which is highly intensive with respect to labor, materials, and cost; in addition, the performance of manual grading is poor. The realization of automatic grading is an urgent requirement in the tobacco industry. To address thi...

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Veröffentlicht in:	IEEE access Jg. 11; S. 1
Hauptverfasser:	Lu, Mengyao, Wang, Cong, Wu, Wenbiao, Zhu, Dinglian, Zhou, Qiang, Wang, Zhiyong, Chen, Tian'en, Jiang, Shuwen, Chen, Dong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Assembly lines Bilinear convolutional neural network Convolutional neural networks Crops Deep learning Feature extraction Image classification Image color analysis Image recognition Image segmentation Industrial applications multi-level features Neural networks Semantics Streaming media Tobacco tobacco grading tobacco image classification Visual tasks Visualization
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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