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Multi-Modality Sheep Face Recognition Based on Deep Learning

delete2025-04-11
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OA
AI
S
Sheng Liao
Y
Yan Shu
T
Tian Fang
Y
Yong Zhou
李国庆 封面图
李国庆 (Guoliang Li)
C
Cheng Zhang *
C
Chao Yao *
W
Wang, Zike
C
Che, Longjie
DOI：10.3390/ani15081111delete
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摘要

摘要

En 中文
为解决同类型羊脸识别的挑战，该类型羊脸具有显著相似性，且RGB图像在不同光照条件和角度下表现各异，本文提出了一种基于ResNet18架构的双分支多模态羊脸识别模型。该模型能够有效学习深度数据的几何特征和RGB数据的纹理特征，从而提升识别精度。初始阶段，模型采用两个InceptionV2层，分别针对RGB通道和深度通道，以提取两种模态的特定特征。随后计算两种模态的损失值。在中期阶段，采用卷积块注意力模块（CBAM）融合两种模态，在最终阶段则利用残差网络学习模态间的互补特征。实验结果表明，该模型得益于有效的多模态融合，在复杂光照条件和多角度情况下实现了高精度的羊脸识别。
Keyword:
sheep face recognition
multimodal
deep learning
ResNet
CBAM attention

期刊

Animals 封面图
Animals
IF:
2.7
论文数:
6.3K
被引数:
5.1W

机构

J
Jinchang City Animal Husbandry and Veterinary Station Gansu Province
学者数:
1
论文数: 1
被引数: 0
G
gansu anim husb technol extens gen stn
学者数:
2
论文数: 1
被引数: 0
引用论文

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