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Multi-channel and multi-scale separable dilated convolutional neural network with attention mechanism for flue-cured tobacco classification

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Abstract

Tobacco classification is a challenging research topic and plays a crucial role in the process of cigarette production. Tobacco classification mainly relies on manual selection, which is time-consuming, labor-intensive, and subjective. With the development of machine learning, how to automatically classify tobacco leaves has become a fast-growing research issue. However, the lack of high-quality tobacco image dataset limits the applications of deep learning approaches seriously. In addition, a large number of parameters, single-scale features, and high computational complexity further affect the classification results. To address these problems, we establish a new tobacco dataset, which contains 11849 labeled tobacco leaf images in 9 categories. Then, a multi-channel and multi-scale separable dilated convolution neural network with attention mechanism is proposed. The adopted separable dilated convolution increases the receptive fields of the convolution kernels and improves the calculation speed and accuracy of the model without increasing the number of training parameters. Then, the attention mechanism is integrated, so that the network can assign higher weights for discriminative features and get rid of redundant ones by assigning lower even zero weights. Experimental results demonstrate the superiority and effectiveness of the proposed approach. Based on our new dataset, the average classification result of the proposed method achieves 98.4%.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Author notes

  1. Jinfeng Gao, Zhong Zhang, and Xin Guo have contributed equally to this work.

Authors and Affiliations

  1. School of Electrical and Information Engineering, Zhengzhou University, Kexue Road NO. 100, Zhengzhou, 450001, China

    Ming Xu, Jinfeng Gao, Zhong Zhang & Xin Guo

  2. School of Electronic and Information Engineering, Zhongyuan University of Technology, Huaihe Road NO.1, Zhengzhou, 451191, China

    Ming Xu

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  1. Ming Xu
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  2. Jinfeng Gao
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  3. Zhong Zhang
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  4. Xin Guo
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Correspondence to Zhong Zhang.

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Xu, M., Gao, J., Zhang, Z. et al. Multi-channel and multi-scale separable dilated convolutional neural network with attention mechanism for flue-cured tobacco classification. Neural Comput & Applic 35, 15511–15529 (2023). https://doi.org/10.1007/s00521-023-08544-7

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  • DOI: https://doi.org/10.1007/s00521-023-08544-7

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