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Advancing AI-based species identification for marine bycatch monitoring: Insights from faster R-CNN experiments
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DOI：10.1016/j.ecoinf.2026.103960.png)
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Abstract
En 中文
• Faster R-CNN reliably detects high-risk taxa in operational settings. • Dataset-tuned anchors reduce misidentifications among visually similar taxa. • A modular two-model AI workflow pairs fast screening with refined classification. • The approach supports scalable, auditable bycatch monitoring.
Keywords:
Bycatch
Biodiversity monitoring
Deep learning
Computer vision
Faster R-CNN
YOLO
Object detection
Fisheries
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