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Segmentation

Papers

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Showing 4526–4550 of 13072 papers

TitleStatusHype
Cell Segmentation and Tracking using CNN-Based Distance Predictions and a Graph-Based Matching StrategyCode0
Anytime, Anywhere, Anyone: Investigating the Feasibility of Segment Anything Model for Crowd-Sourcing Medical Image AnnotationsCode0
Cellpose+, a morphological analysis tool for feature extraction of stained cell imagesCode0
Machine learning approach for segmenting glands in colon histology images using local intensity and texture featuresCode0
CellPilotCode0
Instance Segmentation of Microscopic ForaminiferaCode0
Intensity Confusion Matters: An Intensity-Distance Guided Loss for Bronchus SegmentationCode0
Interactive Segmentation for Diverse Gesture Types Without ContextCode0
Instance Segmentation by Deep ColoringCode0
Instance Segmentation as Image Segmentation AnnotationCode0
CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image SegmentationCode0
Instance-level quantitative saliency in multiple sclerosis lesion segmentationCode0
C-DLinkNet: considering multi-level semantic features for human parsingCode0
3D Densely Convolutional Networks for Volumetric SegmentationCode0
Instance Segmentation for Whole Slide Imaging: End-to-End or Detect-Then-SegmentCode0
InsMix: Towards Realistic Generative Data Augmentation for Nuclei Instance SegmentationCode0
InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-PastingCode0
CCNet: Criss-Cross Attention for Semantic SegmentationCode0
An Underwater Image Semantic Segmentation Method Focusing on Boundaries and a Real Underwater Scene Semantic Segmentation DatasetCode0
Infrastructure Crack Segmentation: Boundary Guidance Method and Benchmark DatasetCode0
C-CAM: Causal CAM for Weakly Supervised Semantic Segmentation on Medical ImageCode0
A Benchmark of Long-tailed Instance Segmentation with Noisy LabelsCode0
Instance-aware Semantic Segmentation via Multi-task Network CascadesCode0
Influence of Early through Late Fusion on Pancreas Segmentation from Imperfectly Registered Multimodal MRICode0
CBAR‑UNet: A novel methodology for segmentation of cardiac magnetic resonance images using block attention‑based deep residual neural networkCode0
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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