SOTAVerified

Segmentation

Papers

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Showing 10426–10450 of 13072 papers

TitleStatusHype
Improving the Segmentation of Pediatric Low-Grade Gliomas through Multitask Learning—0
Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl—0
NuClick: From Clicks in the Nuclei to Nuclear Boundaries—0
Improving Topic Segmentation by Injecting Discourse Dependencies—0
Improving Training on Noisy Stuctured Labels—0
Improving Uncertainty-based Out-of-Distribution Detection for Medical Image Segmentation—0
NUDF: Neural Unsigned Distance Fields for high resolution 3D medical image segmentation—0
An End-to-End Network for Panoptic Segmentation—0
Improving Unsupervised Stain-To-Stain Translation using Self-Supervision and Meta-Learning—0
Improving Unsupervised Video Object Segmentation with Motion-Appearance Synergy—0
Improving Vertebra Segmentation through Joint Vertebra-Rib Atlases—0
NudgeSeg: Zero-Shot Object Segmentation by Repeated Physical Interaction—0
An End-to-End learnable Flow Regularized Model for Brain Tumor Segmentation—0
Improving Whole Slide Segmentation Through Visual Context - A Systematic Study—0
IMS at the CoNLL 2017 UD Shared Task: CRFs and Perceptrons Meet Neural Networks—0
3D Segmentation Networks for Excessive Numbers of Classes: Distinct Bone Segmentation in Upper Bodies—0
Incomplete hippocampal inversion and hippocampal subfield volumes: Implementation and inter-reliability of automatic segmentation—0
Incomplete Multi-modal Brain Tumor Segmentation via Learnable Sorting State Space Model—0
Incomplete Utterance Rewriting as Semantic Segmentation—0
An End-to-end Entangled Segmentation and Classification Convolutional Neural Network for Periodontitis Stage Grading from Periapical Radiographic Images—0
An End to End Deep Neural Network for Iris Segmentation in Unconstraint Scenarios—0
An End-to-End Approach for Recognition of Modern and Historical Handwritten Numeral Strings—0
In-context learning for medical image segmentation—0
In-Context Translation: Towards Unifying Image Recognition, Processing, and Generation—0
Incorporating Boundary Uncertainty into loss functions for biomedical image segmentation—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