1 code implementation • 20 Apr 2024 • Yang Yang, Shunyi Zheng
The advancement of deep learning has driven notable progress in remote sensing semantic segmentation.
1 code implementation • 15 Feb 2022 • Wei Ao, Shunyi Zheng, Yan Meng
In this paper, we introduce a mask-based classification method for addressing this problem.
1 code implementation • IEEE Transactions on Geoscience and Remote Sensing 2021 • Rui Li, Shunyi Zheng, Ce Zhang, Chenxi Duan, Jianlin Su, Libo Wang, Peter M. Atkinson
A novel attention mechanism of kernel attention with linear complexity is proposed to alleviate the large computational demand in attention.
Ranked #7 on Semantic Segmentation on ISPRS Vaihingen
2 code implementations • 16 Feb 2021 • Rui Li, Shunyi Zheng, Ce Zhang, Chenxi Duan, Libo Wang
Based on FPN and AAM, a novel framework named Attention Aggregation Feature Pyramid Network (A2-FPN) is developed for semantic segmentation of fine-resolution remotely sensed images.
1 code implementation • 29 Nov 2020 • Rui Li, Shunyi Zheng, Chenxi Duan, Jianlin Su, Ce Zhang
The attention mechanism can refine the extracted feature maps and boost the classification performance of the deep network, which has become an essential technique in computer vision and natural language processing.
no code implementations • 3 Sep 2020 • Rui Li, Shunyi Zheng, Chenxi Duan, Ce Zhang, Jianlin Su, P. M. Atkinson
A novel attention mechanism of kernel attention with linear complexity is proposed to alleviate the large computational demand in attention.
1 code implementation • 1 Aug 2020 • Rui Li, Shunyi Zheng, Chenxi Duan, Ce Zhang
In this paper, a Multi-Scale Fully Convolutional Network (MSFCN) with multi-scale convolutional kernel is proposed to exploit discriminative representations from two-dimensional (2D) satellite images.
2 code implementations • 29 Jul 2020 • Rui Li, Jianlin Su, Chenxi Duan, Shunyi Zheng
In this paper, to remedy this deficiency, we propose a Linear Attention Mechanism which is approximate to dot-product attention with much less memory and computational costs.
2 code implementations • 26 Jul 2020 • Rui Li, Chenxi Duan, Shunyi Zheng, Ce Zhang, Peter M. Atkinson
In this Letter, we incorporate multi-scale features generated by different layers of U-Net and design a multi-scale skip connected and asymmetric-convolution-based U-Net (MACU-Net), for segmentation using fine-resolution remotely sensed images.