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Spectral-YOLOv13: A Dual-Domain Vision-Mamba Sensing Framework for Fine-Grained Coral Health Assessment and
Litian Yang1, Wenkun Chen2, Zhuoyue Mo2
1College of Mathematics and Informatics, South China Agricultural University, Guangzhou 510642, China.
Sensors (Basel, Switzerland)
|May 27, 2026
Summary
We developed Spectral-YOLOv13, an AI framework for monitoring coral reefs. It improves health assessment and predicts ecological changes in turbid waters, aiding conservation efforts.
Area of Science:
- Marine Biology
- Artificial Intelligence
- Ecosystem Monitoring
Background:
- Coral reefs are vital but vulnerable marine ecosystems.
- Current AI monitoring faces challenges like turbidity, difficulty distinguishing coral health states, and discrete forecasting.
- Effective conservation requires advanced underwater visual monitoring.
Purpose of the Study:
- To introduce Spectral-YOLOv13, a dual-domain vision-Mamba sensing framework.
- To enhance coral health evaluation precision and enable continuous ecological forecasting.
- To overcome limitations of existing AI-powered underwater monitoring systems.
Main Methods:
- Proposed Spectral-YOLOv13 framework with three novel components: Wavelet-Integrated Omni-Neck (WIO-Neck), Contrastive Prototype Head (CP-Head), and Bio-Mamba Predictor.
- WIO-Neck for multi-scale spectral filtering and noise suppression.
- CP-Head for improved discrimination of coral health states and Bio-Mamba Predictor for continuous health trajectory analysis.
Main Results:
- Spectral-YOLOv13 achieved 53.8% mAP with robustness in turbid conditions.
- Reduced four-week forecasting error by 26.8%.
- Maintained real-time inference speed at 112 FPS.
Conclusions:
- Spectral-YOLOv13 offers a reliable and high-performance solution for underwater coral reef monitoring.
- The framework supports precise health evaluation and continuous ecological forecasting.
- This technology aids proactive conservation management of marine ecosystems.
Keywords:
continuous ecological forecastingcoral health monitoringfine-grained ecological classificationintelligent sensing systemprecision ecological sensingreal-time object detectionstate space modelsunderwater roboticsunderwater vision sensingMore Related Videos
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