Intelligent application of interactive scale transformer for fine grained feature extraction in sheep

文献类型： 外文期刊

第一作者： Guo, Xingran

作者： Guo, Xingran;Yu, Haizheng;Liao, Xueying;Zhu, Yongqi;Yu, Haizheng;Bian, Hong;Li, Wenrong

作者机构：

关键词： Sheep detection; Artificial intelligence application; Identity document classification; Kinship recognition; Attention mechanism

期刊名称：ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE （ 影响因子：8.0； 五年影响因子：7.7 ）

ISSN： 0952-1976

年卷期： 2025 年 147 卷

页码：

收录情况： SCI

摘要： In modern animal husbandry, artificial intelligence helps accurately manage individual sheep. However, it is difficult to recognize the sheep's facial features and capture the nuances. It is not easy to extract the fine-grained features of a sheep's face because the traditional vision transformer cannot realize the effective embedding of the interaction scale. To address this problem, we propose a novel sheep Transformer tool called SheepFormer. This model comprises components such as the Interactive Scale Embedded Images Block (ISEI), Patch Short Long Distance Attention Module (PSLDA), Dynamic Relative Position Offset (DRPO), and Transformer Neck and Head (TNH). These components are designed to embed features at multiple scales, fuse long and short-distance self-attention, adaptively handle relative position offsets for various group sizes, and introduce a prediction head to detect fine-grained facial targets in sheep at different scales. SheepFormer integrates Residual Attention to seek dense facial features in sheep and utilizes a Transformer Head to replace the traditional head, exploring the predictive potential of self-attention mechanisms in sheep faces. Experimental results demonstrate a 7.1% improvement in average precision (AP) for sheep face detection compared to Collaborative DEtection TRansformer (CO-DETR) and an 11.12% enhancement inaccurate classification of sheep identity document (ID) compared to Shifted Windows Transformer (Swin Transformer). This study demonstrates that SheepFormer can extract fine-grained facial features of sheep, which promotes the advancement of high-precision sheep individual recognition and provides a guide for recognizing kinship.

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