A Spatial and Semantic Alignment Fusion Network for SeaLand Port Segmentation

A Spatial and Semantic Alignment Fusion Network for SeaLand Port Segmentation

To address the issues of complex backgrounds and poor segmentation performance for small ship objects in sea–land port areas, we propose a sea–land port segmentation algorithm based on spatial and semantic alignment fusion. The algorithm utilizes parallel Transformer&#x2013...

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Bibliographic Details
Main Authors: Bo Zhang, Yaxiong Chen, Weichong Dang, Shengwu Xiong, Xiaoqiang Lu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Convolutional neural network (CNN)
feature alignment
feature fusion
sea–land port segmentation
transformer
Online Access:https://ieeexplore.ieee.org/document/10897902/
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