An Efficient Cascaded Model for Ship Segmentation in Aerial Images

An Efficient Cascaded Model for Ship Segmentation in Aerial Images

In this work, we propose a new method for real-time ship segmentation during maritime surveillance missions using aircrafts with onboard video cameras. We propose a cascade model with a detection stage followed by a segmentation stage. The detection stage selects candidate regions (bounding boxes) l...

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Bibliographic Details
Main Authors: Carlos Pires, Bruno Damas, Alexandre Bernardino
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Maritime surveillance
ship detection
ship segmentation
real-time image segmentation
convolutional neural networks
deep learning
Online Access:https://ieeexplore.ieee.org/document/9736587/

Internet

https://ieeexplore.ieee.org/document/9736587/

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