Marine Debris Detection in Satellite Surveillance using Attention Mechanisms

TL;DR

This study enhances marine debris detection in satellite images by integrating YOLOv7 with attention mechanisms, finding CBAM to be the most effective model for accurate localization and segmentation.

Contribution

It introduces a novel combination of YOLOv7 with various attention mechanisms, identifying CBAM as the most effective for marine debris detection in satellite imagery.

Findings

CBAM achieved the highest F1 scores in detection and segmentation.

Bottleneck transformer detected some debris missed by manual annotations.

CBAM is most suitable for marine debris detection based on evaluation metrics.

Abstract

Marine debris is an important issue for environmental protection, but current methods for locating marine debris are yet limited. In order to achieve higher efficiency and wider applicability in the localization of Marine debris, this study tries to combine the instance segmentation of YOLOv7 with different attention mechanisms and explores the best model. By utilizing a labelled dataset consisting of satellite images containing ocean debris, we examined three attentional models including lightweight coordinate attention, CBAM (combining spatial and channel focus), and bottleneck transformer (based on self-attention). Box detection assessment revealed that CBAM achieved the best outcome (F1 score of 77%) compared to coordinate attention (F1 score of 71%) and YOLOv7/bottleneck transformer (both F1 scores around 66%). Mask evaluation showed CBAM again leading with an F1 score of 73%, whereas coordinate attention and YOLOv7 had comparable performances (around F1 score of 68%/69%) and bottleneck transformer lagged behind at F1 score of 56%. These findings suggest that CBAM offers optimal suitability for detecting marine debris. However, it should be noted that the bottleneck transformer detected some areas missed by manual annotation and displayed better mask precision for larger debris pieces, signifying potentially superior practical performance.