Boundary-Aware Bias Loss for Transformer-Based Aerial Image Segmentation Model
Author:
Affiliation:
1. Chongqing University of Posts and Telecommunications,Chongqing Key Laboratory of Image Cognition
2. Peking University,School of Software & Microelectronics
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9745891/9746004/09747074.pdf?arnumber=9747074
Reference17 articles.
1. Semantic Segmentation of Small Objects and Modeling of Uncertainty in Urban Remote Sensing Images Using Deep Convolutional Neural Networks
2. Contour loss: Boundary-aware learning for salient object segmentation;chen,2019
3. Perceptual losses for real-time style transfer and super-resolution;johnson;European Conference on Computer Vision,2016
4. SEMEDA: Enhancing segmentation precision with semantic edge aware loss
5. Conformer: Local Features Coupling Global Representations for Visual Recognition
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