SwinInsSeg: An Improved SOLOv2 Model Using the Swin Transformer and a Multi-Kernel Attention Module for Ship Instance Segmentation

SwinInsSeg: An Improved SOLOv2 Model Using the Swin Transformer and a Multi-Kernel Attention Module for Ship Instance Segmentation

Maritime surveillance is essential for ensuring security in the complex marine environment. The study presents SwinInsSeg, an instance segmentation model that combines the Swin transformer and a lightweight MKA module to segment ships accurately and efficiently in maritime surveillance. Current mode...

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Bibliographic Details
Main Authors: Rabi Sharma, Muhammad Saqib, Chin-Teng Lin, Michael Blumenstein
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Mathematics
Subjects:
instance segmentation
maritime surveillance
convolutional neural network
transformers
attention
Online Access:https://www.mdpi.com/2227-7390/13/1/165
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