Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:19:04.869698Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 100 of 109 outbound references and 0 inbound Pith citation observations for arXiv:2506.05917.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:19:04.869698Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
100 of 109 outbound references displayed
External citation measurements
No source-named external measurement is stored.
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Information fusion76, 243–297 (2021)
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: Proceedings of the IEEE conference on computer vision and pattern recognition
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness IEEE transactions on pattern analysis and machine intelligence40(4), 834–848 (2017)
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Advances in neural in- formation processing systems33, 22243–22255 (2020)
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: European Conference on Computer Vision
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Unresolved cited work
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Observation 3ec4f48d-87d6-43c7-a99c-1d74f4d31aa9 · outbound
Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Journal of Open Source Software7(70), 4101 (2022)
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: Proceedings of the IEEE/CVF International Conference on Computer Vision
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness International journal of computer vision111, 98–136 (2015) 14 S
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Pattern Recognition130, 108777 (2022)
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Semi-supervised semantic segmentation needs strong, varied perturbations
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Advances in neural information processing systems27(2014)
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Explaining and Harnessing Adversarial Examples
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: International Conference on Machine Learning
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: Proceedings of the IEEE conference on computer vision and pattern recognition
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: Proceedings of the IEEE/CVF International Conference on Computer Vision
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Improving neural networks by preventing co-adaptation of feature detectors
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: Eu- ropean Conference on Computer Vision
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: European Conference on Computer Vision
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: Proceedings of the IEEE/CVF Conference on computer vision and pattern recognition
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Adversarial Learning for Semi-Supervised Semantic Segmentation
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: 2019 IEEE/CVF International Conference on Computer Vision Work- shop (ICCVW)
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Information Processing & Management58(5), 102680 (2021) Rethinking Semi-supervised Segmentation Beyond Accuracy 15
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Advances in Neural Information Processing Systems35, 2803– 2816 (2022)
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness International journal of computer vision129(2), 462–483 (2021)
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Advances in neural information processing systems32 (2019)
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness tm-Technisches Messen (2025)
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness ISPRS Annals of the Photogrammetry, Re- mote Sensing and Spatial Information Sciences10, 129–136 (2024)
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness A Critical Synthesis of Uncertainty Quantification and Foundation Models in Monocular Depth Estimation
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness PFG–Journal of Photogrammetry, Remote Sensing and Geoinformation Science92(2), 101–114 (2024)
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Neurocomputing338, 321–348 (2019)
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: Proceedings of the IEEE/CVF International Conference on Computer Vision
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Diverse Cotraining Makes Strong Semi-Supervised Segmentor
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: Proceedings of the IEEE/CVF International Conference on Computer Vision
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: Proceedings of the IEEE conference on computer vision and pattern recognition
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness IEEE transactions on pattern analysis and machine intelligence44(7), 3523–3542 (2021)
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness IEEE transactions on pattern analysis and machine intelligence43(4), 1369–1379 (2019)
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness IEEE Transactions on Intelligent Transportation Systems22(7), 4316–4336 (2020)
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness Unresolved cited work
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Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness In: Proceedings of the IEEE/CVF international conference on computer vision
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