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Segmentation

Papers

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Showing 9976–10000 of 13072 papers

TitleStatusHype
Uncertainty-Aware Training of Neural Networks for Selective Medical Image Segmentation—0
Uncertainty-based method for improving poorly labeled segmentation datasets—0
Uncertainty Driven Active Learning for Image Segmentation in Underwater Inspection—0
Uncertainty-driven and Adversarial Calibration Learning for Epicardial Adipose Tissue Segmentation—0
Uncertainty-driven refinement of tumor-core segmentation using 3D-to-2D networks with label uncertainty—0
Uncertainty-driven Sanity Check: Application to Postoperative Brain Tumor Cavity Segmentation—0
Uncertainty-Error correlations in Evidential Deep Learning models for biomedical segmentation—0
Uncertainty estimates for semantic segmentation: providing enhanced reliability for automated motor claims handling—0
Uncertainty estimation in Deep Learning for Panoptic segmentation—0
Uncertainty Estimation in Deep Neural Networks for Point Cloud Segmentation in Factory Planning—0
Uncertainty Estimation in Instance Segmentation with Star-convex Shapes—0
Uncertainty Gated Network for Land Cover Segmentation—0
Uncertainty-Guided Coarse-to-Fine Tumor Segmentation with Anatomy-Aware Post-Processing—0
Uncertainty-Guided Domain Alignment for Layer Segmentation in OCT Images—0
Uncertainty-Guided Mutual Consistency Learning for Semi-Supervised Medical Image Segmentation—0
Uncertainty guided semi-supervised segmentation of retinal layers in OCT images—0
Uncertainty in Minimum Cost Multicuts for Image and Motion Segmentation—0
Uncertainty Modeling in Ultrasound Image Segmentation for Precise Fetal Biometric Measurements—0
Uncertainty Quantification for Bird's Eye View Semantic Segmentation: Methods and Benchmarks—0
Uncertainty Quantification for Eosinophil Segmentation—0
Uncertainty quantification for White Matter Hyperintensity segmentation detects silent failures and improves automated Fazekas quantification—0
Uncertainty Quantification in Machine Learning Based Segmentation: A Post-Hoc Approach for Left Ventricle Volume Estimation in MRI—0
Uncertainty Quantification in Medical Image Segmentation with Multi-decoder U-Net—0
Deep Learning with Uncertainty Quantification for Predicting the Segmentation Dice Coefficient of Prostate Cancer Biopsy Images—0
Weakly Supervised Intracranial Hemorrhage Segmentation with YOLO and an Uncertainty Rectified Segment Anything Model—0
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All datasetsSA-1B.MFSDMMFloodSimGas

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1unSAM+ (Semi-supervised)Average Precision42.8—Unverified
2SAMAverage Precision38.9—Unverified
#ModelMetricClaimedVerifiedStatus
1HNN10%20—Unverified
#ModelMetricClaimedVerifiedStatus
1ABANetF1 Score96.82—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet50 + DeepLabV3+F1 score0.77—Unverified
#ModelMetricClaimedVerifiedStatus
1LangGasIoU0.69—Unverified