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Domain adaptive fruit detection method based on multiple alignments

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成果类型:
期刊论文
作者:
Guo, An;Sun, Kaiqiong;Wang, Meng
通讯作者:
Sun, KQ
作者机构:
[Guo, An; Sun, KQ; Sun, Kaiqiong; Wang, Meng] Wuhan Polytechn Univ, Sch Math & Comp Sci, Wuhan 430023, Peoples R China.
通讯机构:
[Sun, KQ ] W
Wuhan Polytechn Univ, Sch Math & Comp Sci, Wuhan 430023, Peoples R China.
语种:
英文
关键词:
Domain adaptation;deep learning;knowledge distillation;fruit detection
期刊:
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
ISSN:
1064-1246
年:
2023
卷:
45
期:
4
页码:
5837-5851
机构署名:
本校为第一且通讯机构
院系归属:
数学与计算机学院
摘要:
While deep learning based object detection methods have achieved high accuracy in fruit detection, they rely on large labeled datasets to train the model and assume that the training and test samples come from the same domain. This paper proposes a cross-domain fruit detection method with image and feature alignments. It first converts the source domain image into the target domain through an attention-guided generative adversarial network to achieve the image-level alignment. Then, the knowledge distillation with mean teacher model is fused in the yolov5 network to achieve the feature alignme...

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