Samba: Semantic Segmentation of Remotely Sensed Images with State Space Model

High-resolution remotely sensed images pose a challenge for commonly used semantic segmentation methods such as Convolutional Neural Network (CNN) and Vision Transformer (ViT).

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Cite this as

Qinfeng Zhu, Yuanzhi Cai, Yuan Fang, Cheng Chen, Lei Fan, Yihan Yang, Anh Nguyen (2024). Dataset: Samba: Semantic Segmentation of Remotely Sensed Images with State Space Model. https://doi.org/10.57702/fuihapw8

DOI retrieved: December 2, 2024

Additional Info

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Created December 2, 2024
Last update December 2, 2024
Author Qinfeng Zhu
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Yuanzhi Cai
Yuan Fang
Cheng Chen
Lei Fan
Yihan Yang
Anh Nguyen
Homepage https://github.com/zhuqinfeng1999/Samba