Hyperspectral Detection of Soybean Heart-Eating Insect Pests Based on Image Retrieval

Jiang-sheng GUI; Jie HE; Xia-ping FU

doi:10.3964/j.issn.1000-0593(2022)09-2931-04

Spectroscopy and Spectral Analysis, Volume. 42, Issue 9, 2931(2022)

Hyperspectral Detection of Soybean Heart-Eating Insect Pests Based on Image Retrieval

Jiang-sheng GUI1,*... Jie HE1,1; and Xia-ping FU2,2; |Show fewer author(s)

Author Affiliations

¹1. School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, China

²2. Faculty of Mechanical Engineering & Automation, Zhejiang Sci-Tech University, Hangzhou 310018, China;

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Fig. 1. Hyperspectral imaging system

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Fig. 2. Hyperspectral images of soybean samples
(a): Normal soybean; (b): Soybean with egg;(c): Soybean with larvae; (d): Gnawed soybean

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Table 1. Detection results of different classification models in 4-way 5-shot
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Table 1. Detection results of different classification models in 4-way 5-shot
小样本学习模型特征提取模型学习率 5-shot准确率/%
MAML Resnet18 0.01 60.05±0.50
MN Resnet18 0.01 77.65±0.50
3D-RN Resnet18 0.01 82.50±1.50

Table 2. Retrieval performance under different loss functions

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Table 2. Retrieval performance under different loss functions

损失函数	预训练模型	学习率	准确率/%
交叉熵损失	Resnet18-K Resnet18-KM	0.01	75.0±1.00 74.5±1.00
DSHSD^[10]	Resnet18-K Resnet18-KM	0.01	81.0±1.00 81.5±1.50
DH^[7]	Resnet18-K Resnet18-KM	0.01	78.5±1.00 79.5±1.00
DSH^[8]	Resnet18-K Resnet18-KM	0.01	80.5±0.50 81.5±1.00
CSQ^[11]	Resnet18-K Resnet18-KM	0.01	79.0±1.00 80.0±1.00
DCH^[6]	Resnet18-K Resnet18-KM	0.01	85.5±1.00 86.0±1.00

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Jiang-sheng GUI, Jie HE, Xia-ping FU. Hyperspectral Detection of Soybean Heart-Eating Insect Pests Based on Image Retrieval[J]. Spectroscopy and Spectral Analysis, 2022, 42(9): 2931

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