Maize Leaf Disease Recognition Based on Transferred and Improved MobileNetV3

doi:10.11924/j.issn.1000-6850.casb2024-0773

Abstract

Abstract:

In recent years, the application of deep learning algorithms in the field of image recognition has gradually expanded into agricultural production, particularly in the area of crop disease detection. Leveraging transfer learning techniques within deep learning, a method for identifying corn leaf diseases based on an improved MobileNetV3 model has been proposed. Pre-trained weights from the ImageNet dataset were transferred to the target dataset, and the model was further optimized. During the optimization process, the original SE (Squeeze-and-Excitation) module was replaced with a CBAM (Convolutional Block Attention Module) attention module, and dilated convolutions were introduced into the convolutional layers to increase the receptive field. After training, an optimal model for corn leaf disease identification was obtained. After applying transfer learning, the model's accuracy on the training set increased from 96.30% to 98.20%, with an improvement of 1.9 percentage points. With further optimization, the accuracy reached 99.09%, demonstrating improved classification performance. This enhancement not only retains the lightweight characteristics of MobileNetV3 but also significantly boosts the performance of corn leaf disease identification.

Key words: corn disease identification, transfer learning, MobileNetV3, attention mechanism

JIN Yuchun, ZHEN Yuanyuan, LIU Ping. Maize Leaf Disease Recognition Based on Transferred and Improved MobileNetV3[J]. Chinese Agricultural Science Bulletin, 2025, 41(23): 145-154.

Figures/Tables 16

References 27

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输入尺寸（高×宽×通道数）	卷积操作	扩展尺寸	输出通道	SE模块	激活函数	步长
224×224×3	conv2d	-	16	-	HS	2
112×112×16	bneck，3×3	16	16	-	RE	1
112×112×16	bneck，3×3	64	24	-	RE	2
56×56×24	bneck，3×3	72	24	-	RE	1
56×56×24	bneck，5×5	72	40	√	RE	2
28×28×40	bneck，5×5	120	40	√	RE	1
28×28×40	bneck，5×5	120	40	√	RE	1
28×28×40	bneck，3×3	240	80	-	HS	2
14×14×80	bneck，3×3	200	80	-	HS	1
14×14×80	bneck，3×3	184	80	-	HS	1
14×14×80	bneck，3×3	184	80	-	HS	1
14×14×80	bneck，3×3	480	112	√	HS	1
14×14×112	bneck，3×3	672	112	√	HS	1
14×14×112	bneck，5×5	672	160	√	HS	2
7×7×160	bneck，5×5	960	160	√	HS	1
7×7×160	bneck，5×5	960	160	√	HS	1
7×7×160	conv2d，1×1	-	900	-	HS	1
7×7×960	pool，7×7	-	-	-	-	1
1×1×960	conv2d，1×1，NBN	-	1280	-	HS	1
1×1×1280	conv2d，1×1，NBN	-	k	-	-	1

输入尺寸（高×宽×通道数）	卷积操作	扩展尺寸	输出通道	SE模块	激活函数	步长
224×224×3	conv2d	-	16	-	HS	2
112×112×16	bneck，3×3	16	16	-	RE	1
112×112×16	bneck，3×3	64	24	-	RE	2
56×56×24	bneck，3×3	72	24	-	RE	1
56×56×24	bneck，5×5	72	40	√	RE	2
28×28×40	bneck，5×5	120	40	√	RE	1
28×28×40	bneck，5×5	120	40	√	RE	1
28×28×40	bneck，3×3	240	80	-	HS	2
14×14×80	bneck，3×3	200	80	-	HS	1
14×14×80	bneck，3×3	184	80	-	HS	1
14×14×80	bneck，3×3	184	80	-	HS	1
14×14×80	bneck，3×3	480	112	√	HS	1
14×14×112	bneck，3×3	672	112	√	HS	1
14×14×112	bneck，5×5	672	160	√	HS	2
7×7×160	bneck，5×5	960	160	√	HS	1
7×7×160	bneck，5×5	960	160	√	HS	1
7×7×160	conv2d，1×1	-	900	-	HS	1
7×7×960	pool，7×7	-	-	-	-	1
1×1×960	conv2d，1×1，NBN	-	1280	-	HS	1
1×1×1280	conv2d，1×1，NBN	-	k	-	-	1

输入尺寸（高×宽×通道数）	卷积操作	扩展尺寸	输出通道	SE模块	激活函数	步长
224×224×3	conv2d，3×3	-	16	-	HS	2
112×112×16	bneck，3×3	16	16	√	RE	2
56×56×16	bneck，3×3	72	24	-	RE	2
28×28×24	bneck，3×3	88	24	-	RE	1
28×28×24	bneck，5×5	96	40	√	HS	2
14×14×40	bneck，5×5	240	40	√	HS	1
14×14×40	bneck，5×5	240	40	√	HS	1
14×14×40	bneck，5×5	120	48	√	HS	1
14×14×48	bneck，5×5	144	48	√	HS	1
14×14×48	bneck，5×5	288	96	√	HS	2
7×7×96	bneck，5×5	576	96	√	HS	1
7×7×96	bneck，5×5	576	96	√	HS	1
7×7×96	conv2d，1×1	-	576	√	HS	1
7×7×576	pool，7×7	-	-	-	-	1
1×1×576	conv2d，1×1，NBN	-	1024	-	HS	1
1×1×1024	conv2d，1×1，NBN	-	k	-	-	1

输入尺寸（高×宽×通道数）	卷积操作	扩展尺寸	输出通道	SE模块	激活函数	步长
224×224×3	conv2d，3×3	-	16	-	HS	2
112×112×16	bneck，3×3	16	16	√	RE	2
56×56×16	bneck，3×3	72	24	-	RE	2
28×28×24	bneck，3×3	88	24	-	RE	1
28×28×24	bneck，5×5	96	40	√	HS	2
14×14×40	bneck，5×5	240	40	√	HS	1
14×14×40	bneck，5×5	240	40	√	HS	1
14×14×40	bneck，5×5	120	48	√	HS	1
14×14×48	bneck，5×5	144	48	√	HS	1
14×14×48	bneck，5×5	288	96	√	HS	2
7×7×96	bneck，5×5	576	96	√	HS	1
7×7×96	bneck，5×5	576	96	√	HS	1
7×7×96	conv2d，1×1	-	576	√	HS	1
7×7×576	pool，7×7	-	-	-	-	1
1×1×576	conv2d，1×1，NBN	-	1024	-	HS	1
1×1×1024	conv2d，1×1，NBN	-	k	-	-	1

真实情况	预测结果
真实情况	健康叶片	被感染叶片
健康叶片	TP	FN
被感染叶片	FP	TN