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Segmentation

Papers

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Showing 3426–3450 of 13072 papers

TitleStatusHype
Level set image segmentation with velocity term learned from data with applications to lung nodule segmentationCode0
SWDL: Stratum-Wise Difference Learning with Deep Laplacian Pyramid for Semi-Supervised 3D Intracranial Hemorrhage SegmentationCode0
Lung segmentation with NASNet-Large-Decoder NetCode0
Lyrics Segmentation: Textual Macrostructure Detection using ConvolutionsCode0
LSSED: A Robust Segmentation Network for Inflamed Appendix from CT ImagesCode0
From Question to Exploration: Test-Time Adaptation in Semantic Segmentation?Code0
LSMVOS: Long-Short-Term Similarity Matching for Video ObjectCode0
Lucid Data Dreaming for Video Object SegmentationCode0
DeepCO3: Deep Instance Co-Segmentation by Co-Peak Search and Co-Saliency DetectionCode0
Deep CNN ensembles and suggestive annotations for infant brain MRI segmentationCode0
Modality Completion via Gaussian Process Prior Variational Autoencoders for Multi-Modal Glioma SegmentationCode0
Modality-Independent Brain Lesion Segmentation with Privacy-aware Continual LearningCode0
Model-based inexact graph matching on top of CNNs for semantic scene understandingCode0
Low-latency Perception in Off-Road Dynamical Low Visibility EnvironmentsCode0
Frontal Low-rank Random Tensors for Fine-grained Action SegmentationCode0
Low-Shot Learning for the Semantic Segmentation of Remote Sensing ImageryCode0
LoopDA: Constructing Self-loops to Adapt Nighttime Semantic SegmentationCode0
LoRA-PT: Low-Rank Adapting UNETR for Hippocampus Segmentation Using Principal Tensor Singular Values and VectorsCode0
Deep Attentive Features for Prostate Segmentation in 3D Transrectal UltrasoundCode0
Deeply Supervised Active Learning for Finger Bones SegmentationCode0
Automatic segmentation of the femur and tibia bones from X-ray images based on pure dilated residual U-NetCode0
DeepAtlas: Joint Semi-Supervised Learning of Image Registration and SegmentationCode0
Longitudinal diffusion MRI analysis using Segis-Net: a single-step deep-learning framework for simultaneous segmentation and registrationCode0
LU-Net: An Efficient Network for 3D LiDAR Point Cloud Semantic Segmentation Based on End-to-End-Learned 3D Features and U-NetCode0
LOCATE: Self-supervised Object Discovery via Flow-guided Graph-cut and Bootstrapped Self-trainingCode0
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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