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LBFNet: A Tomato Leaf Disease Identification Model Based on Three-Channel Attention Mechanism and Quantitative Pruning

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成果类型:
期刊论文
作者:
Chen, Hailin;Wang, Yi;Jiang, Ping;Zhang, Ruofan;Peng, Jialiang
通讯作者:
Wang, Y
作者机构:
[Wang, Yi; Zhang, Ruofan; Peng, Jialiang; Wang, Y; Chen, Hailin] Hunan Agr Univ, Coll Informat & Intelligence, Changsha 410128, Peoples R China.
[Jiang, Ping] Hunan Agr Univ, Coll Mech & Elect Engn, Changsha 410128, Peoples R China.
通讯机构:
[Wang, Y ] H
Hunan Agr Univ, Coll Informat & Intelligence, Changsha 410128, Peoples R China.
语种:
英文
关键词:
artificial intelligence;three-channel attention mechanism;tomato leaf disease;convolution neural network;deep learning
期刊:
Applied Sciences-Basel
ISSN:
2076-3417
年:
2023
卷:
13
期:
9
页码:
5589-
基金类别:
Conceptualization, H.C. and R.Z.; methodology, H.C.; software, H.C. and J.P.; validation, H.C., R.Z. and J.P.; resources, H.C.; data curation, Y.W.; writing—original draft preparation, H.C. and Y.W.; writing—review and editing, H.C., J.P., R.Z. and Y.W.; supervision, Y.W.; project administration, Y.W. and P.J.; funding acquisition, Y.W.; investigation, H.C. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Key R&D Program of China under the sub-project “Research and System Development of Navigation Technology for Harvesting Machine of Special Economic Crops” (No. 2022YFD2002001) within the key program “Engineering Science and Comprehensive Interdisciplinary Research”.
机构署名:
本校为第一且通讯机构
摘要:
The current neural networks for tomato leaf disease recognition have problems such as large model parameters, long training time, and low model accuracy. To solve these problems, a lightweight convolutional neural network (LBFNet) is proposed in this paper. First, LBFNet is established as the base model. Secondly, a three-channel attention mechanism module is introduced to learn the disease features in tomato leaf disease images and reduce the interference of redundant features. Finally, a cascade module is introduced to increase the depth of the model, solve the gradient descent problem, and ...

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