Influence of Out-of-Distribution Examples on the Quality of Semantic Segmentation in Remote Sensing-Reference-Cited by-同舟云学术

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Influence of Out-of-Distribution Examples on the Quality of Semantic Segmentation in Remote Sensing

Published:2023-07-16 Issue: Volume: Page:
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Container-title:IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Qiu Kevin¹,Bulatov Dimitri¹,Budde Lina E.²,Kullmann Timo²,Iwaszczuk Dorota²

Affiliation:

1. System Technologies and Image Exploitation,Scene Analysis Division Fraunhofer Institute of Optronics,Ettlingen,Germany

2. Technical University of Darmstadt,Civil and Environmental Engineering Sciences Remote Sensing and Image Analysis,Darmstadt,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10281394/10281399/10282990.pdf?arnumber=10282990

Reference15 articles.

1. Imagenet: A large-scale hierarchical image database;deng;IEEE Conference on Computer Vision and Pattern Recognition,2009

2. Deep residual learning for image recognition;he;2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016

3. Segmentation models pytorch;yakubovskiy,2020

4. Fixing weight decay regularization in adam;loshchilov;CoRR,2017

5. Encoder-decoder with atrous separable convolution for semantic image segmentation;chen;CoRR,2018

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Characterization of Out-of-distribution Samples from Uncertainty Maps Using Supervised Machine Learning;Lecture Notes in Computer Science;2024

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