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<p>Real-time screening of surface-associated health abnormalities in fish is crucial for controlling disease outbreaks in aquaculture and mitigating the economic losses caused by fish diseases. The active movement of fish schools and the generally fine-grained characteristics of fish body surface symptoms make it challenging for conventional methods to accurately monitor fish health without causing physical harm. In this paper, we propose RT-GalaDet, a real-time detection method for abnormal fish surface health features, based on an improved RT-DETR model. By incorporating a triple design of State Space Modeling, Local Enhancement, and Lightweight Neck Compression, the model achieves end-to-end real-time inference while maintaining high accuracy and is designed for computationally lightweight real-time processing. Experimental results show that RT-GalaDet achieves Precision, Recall, <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\text {mAP}_{50}\)</EquationSource> </InlineEquation>, <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\text {mAP}_{50-95}\)</EquationSource> </InlineEquation> and <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\text {FPS}\)</EquationSource> </InlineEquation> of <InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(93.3\%\)</EquationSource> </InlineEquation>, <InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(89.7\%\)</EquationSource> </InlineEquation>, <InlineEquation ID="IEq6"> <EquationSource Format="TEX">\(89.0\%\)</EquationSource> </InlineEquation>, <InlineEquation ID="IEq7"> <EquationSource Format="TEX">\(79.0\%\)</EquationSource> </InlineEquation> and 51.98, respectively. This work presents a fast, non-invasive real-time screening method for surface-associated health abnormalities in fish, providing aquaculture staff with reliable alerts and localized evidence to support further professional diagnosis and timely intervention.</p>

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RT-GalaDet as a real-time model for screening surface-associated health abnormalities in fish

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月2日

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  • Xiaohong Peng,
  • Zhuohan Xiao,
  • Yinghuai Yu

摘要

Real-time screening of surface-associated health abnormalities in fish is crucial for controlling disease outbreaks in aquaculture and mitigating the economic losses caused by fish diseases. The active movement of fish schools and the generally fine-grained characteristics of fish body surface symptoms make it challenging for conventional methods to accurately monitor fish health without causing physical harm. In this paper, we propose RT-GalaDet, a real-time detection method for abnormal fish surface health features, based on an improved RT-DETR model. By incorporating a triple design of State Space Modeling, Local Enhancement, and Lightweight Neck Compression, the model achieves end-to-end real-time inference while maintaining high accuracy and is designed for computationally lightweight real-time processing. Experimental results show that RT-GalaDet achieves Precision, Recall, \(\text {mAP}_{50}\) , \(\text {mAP}_{50-95}\) and \(\text {FPS}\) of \(93.3\%\) , \(89.7\%\) , \(89.0\%\) , \(79.0\%\) and 51.98, respectively. This work presents a fast, non-invasive real-time screening method for surface-associated health abnormalities in fish, providing aquaculture staff with reliable alerts and localized evidence to support further professional diagnosis and timely intervention.