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M²S-YOLOv8: Detección de Buques Multiescala y Consciente de la Asimetría para Entornos Marinos
Peizheng Li1,2, Dayong Qiao1, Jianyi Mu2
1School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China.
Sensors (Basel, Switzerland)
|January 28, 2026
Resumen
Este estudio presenta M2S-YOLOv8, un marco mejorado de detección de buques. Mejora la precisión en condiciones marinas difíciles y ofrece una implementación eficiente en plataformas marinas no tripuladas.
Sus antecedentes:
- La detección de buques es crucial para la percepción del medio ambiente marino, pero enfrenta desafíos como la oclusión de objetivos, objetivos multiescala, geometrías asimétricas y condiciones de imagen adversas.
- Los métodos existentes basados en la visión tienen dificultades con la calidad degradada de la imagen y los escenarios complejos comunes en los entornos marinos reales.
Objetivo del estudio:
- Desarrollar un marco mejorado de detección de buques, M2S-YOLOv8, que aborde las limitaciones de los métodos actuales en entornos marinos complejos.
- Mejorar la percepción de objetivos de buques multiescala y asimétricos, mejorar la eficiencia de la fusión de características y estabilizar la regresión de objetivos pequeños.
Principales métodos:
- Se propuso el marco M2S-YOLOv8 basado en YOLOv8, que incorpora un módulo de Atención Paralelizada por Parches Consciente de la Asimetría Multiescala (MSA-PPA) en la columna vertebral.
- Se introdujo un operador de Upsampling de Convolución Deformable (DCNUpsample) en el Cuello para una fusión adaptativa eficiente de características.
- Se desarrolló una función de pérdida CIoU normalizada ponderada por distancia de Wasserstein (WA-CIoU) para mejorar la estabilidad de la regresión de objetivos pequeños.
Principales resultados:
- M2S-YOLOv8 demostró un rendimiento mejorado en el Conjunto de Datos de Percepción de Buques No Tripulados (UZPD) y el Conjunto de Datos Marítimos de Singapur (SMD).
- El marco logró un equilibrio entre el diseño ligero y las capacidades de inferencia en tiempo real.
- Se observó una percepción mejorada de objetivos multiescala y asimétricos, fusión eficiente de características y localización estable.
Conclusiones:
- M2S-YOLOv8 ofrece una solución robusta para la detección de buques en entornos marinos desafiantes.
- Las mejoras propuestas mejoran significativamente la precisión de la detección y la estabilidad de la localización.
- El marco muestra un gran potencial para su implementación en dispositivos de borde de plataformas marinas no tripuladas para una percepción marina confiable.
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