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Segmentation

Papers

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Showing 5751–5775 of 13072 papers

TitleStatusHype
FVP: Fourier Visual Prompting for Source-Free Unsupervised Domain Adaptation of Medical Image Segmentation—0
A Geometric Flow Approach for Segmentation of Images with Inhomongeneous Intensity and Missing Boundaries—0
Icon: An Interactive Approach to Train Deep Neural Networks for Segmentation of Neuronal Structures—0
ICPR 2024 Competition on Multiple Sclerosis Lesion Segmentation -- Methods and Results—0
A dynamic graph-cuts method with integrated multiple feature maps for segmenting kidneys in ultrasound images—0
IDA: Informed Domain Adaptive Semantic Segmentation—0
IDDA: a large-scale multi-domain dataset for autonomous driving—0
Contrastive Learning for Label-Efficient Semantic Segmentation—0
MedUHIP: Towards Human-In-the-Loop Medical Segmentation—0
FVOS for MOSE Track of 4th PVUW Challenge: 3rd Place Solution—0
Fuzzy Superpixel-based Image Segmentation—0
Identifying Alzheimer Disease Dementia Levels Using Machine Learning Methods—0
Identifying Most Walkable Direction for Navigation in an Outdoor Environment—0
Identifying Reliable Annotations for Large Scale Image Segmentation—0
Fuzzy Segmentations of a String—0
Identify the cells' nuclei based on the deep learning neural network—0
Fuzzy Rank-based Late Fusion Technique for Cytology image Segmentation—0
IDPL: Intra-subdomain adaptation adversarial learning segmentation method based on Dynamic Pseudo Labels—0
Coarse-to-Fine Domain Adaptive Semantic Segmentation with Photometric Alignment and Category-Center Regularization—0
ASC-Net: Unsupervised Medical Anomaly Segmentation Using an Adversarial-based Selective Cutting Network—0
IGL-DT: Iterative Global-Local Feature Learning with Dual-Teacher Semantic Segmentation Framework under Limited Annotation Scheme—0
IGraSS: Learning to Identify Infrastructure Networks from Satellite Imagery by Iterative Graph-constrained Semantic Segmentation—0
IKEA-Manual: Seeing Shape Assembly Step by Step—0
Contrastive Rendering for Ultrasound Image Segmentation—0
Fuzzy Clustering Based Segmentation Of Vertebrae in T1-Weighted Spinal MR Images—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