基于残差卷积神经网络模型的勺嘴鹬动作识别

YANG Xueke,MENG Jinchao,FENG Yueheng, LIN Tingting, WANG Zhaojun,LIU Hui

Journal of Tropical Biology（2023）

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Abstract

为开启海南热带地区鸻鹬类涉禽的动作识别以及其他野生鸟类行为学自动识别的研究,建立了基于野外采集影像的勺嘴鹬(Eurynorhynchus pygmeus)动作图像数据集.该数据集由表达勺嘴鹬主要行为模式的 9种动作标签组成;同时利用ResNet50、ResNet101和ResNet152共 3种残差卷积神经网络模型尝试对勺嘴鹬的动作进行自动识别.结果表明,ResNet50、ResNet101、ResNet152测试集准确率分别为 96.90%、96.94%和96.90%,说明3种模型都能对勺嘴鹬图像进行快速准确的动作识别.

Key words

residual convolutional neural network,bird image,movement recognition,spoon-billed sandpiper

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