Jan 4, 2024 · In this article, a new semantic segmentation net framework named SSNet is proposed, which incorporates an encoder–decoder structure, optimizing ...
Jan 16, 2024 · In this article, a new semantic segmentation net framework named SSNet is proposed, which incorporates an encoder–decoder structure, optimizing ...
In this paper, a new semantic segmentation net framework named SSNet is proposed, which incorporates an encoder-decoder structure, optimizing the advantages ...
SSNet: A Novel Transformer and CNN Hybrid Network for Remote Sensing Semantic Segmentation · Yao, Min · Zhang, Yaozu · Liu, Guofeng · Pang, Dongdong ...
Sep 8, 2024 · Transformer together with convolutional neural network (CNN) has achieved better performance than the pure module-based methods.
In this paper, an asymmetric network (CTANet), which combines the advantages of CNN and Transformer, is proposed to achieve efficient extraction of buildings.
The proposed hybrid network achieved the second highest overall accuracy (OA) on both the Potsdam and Vaihingen benchmarks and is compared with the current ...
Missing: SSNet: | Show results with:SSNet:
Pang, “SSNet: A novel transformer and CNN hybrid network for remote sensing seman- tic segmentation,” IEEE Journal of Selected Topics in Applied. Earth ...
Sep 26, 2024 · We propose a semantic segmentation framework for high-resolution remotely sensed imagery, named Samba. Samba utilizes an encoder-decoder architecture.
The method proposed in this paper is essentially a hybrid network based on CNN and Transformer, specifically optimized for the distinctive challenges in the RSI ...