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Segmentation

Papers

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Showing 4751–4775 of 13072 papers

TitleStatusHype
S4: Self-Supervised Sensing Across the Spectrum—0
Image segmentation of treated and untreated tumor spheroids by Fully Convolutional Networks—0
Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and Beyond: A Survey—0
Zero-Shot Monocular Motion Segmentation in the Wild by Combining Deep Learning with Geometric Motion Model Fusion—0
Lane Segmentation Refinement with Diffusion Models—0
Predictive Accuracy-Based Active Learning for Medical Image SegmentationCode0
MMTryon: Multi-Modal Multi-Reference Control for High-Quality Fashion Generation—0
SpecstatOR: Speckle statistics-based iOCT Segmentation Network for Ophthalmic Surgery—0
DELINE8K: A Synthetic Data Pipeline for the Semantic Segmentation of Historical DocumentsCode0
Real Time Multi Organ Classification on Computed Tomography Images—0
Clicks2Line: Using Lines for Interactive Image Segmentation—0
Panoptic Segmentation and Labelling of Lumbar Spine Vertebrae using Modified Attention Unet—0
Rethinking Attention Gated with Hybrid Dual Pyramid Transformer-CNN for Generalized Segmentation in Medical ImagingCode0
Segmentation Quality and Volumetric Accuracy in Medical Imaging—0
GLIMS: Attention-Guided Lightweight Multi-Scale Hybrid Network for Volumetric Semantic SegmentationCode0
Optimizing Universal Lesion Segmentation: State Space Model-Guided Hierarchical Networks with Feature Importance Adjustment—0
Quantum Patch-Based Autoencoder for Anomaly SegmentationCode0
Discriminative features pyramid network for medical image segmentationCode0
Discriminative features pyramid network for medical image segmentationCode0
RadGenome-Chest CT: A Grounded Vision-Language Dataset for Chest CT AnalysisCode0
DiffSeg: A Segmentation Model for Skin Lesions Based on Diffusion Difference—0
Multi-view Cardiac Image Segmentation via Trans-Dimensional Priors—0
Semantic Segmentation Refiner for Ultrasound Applications with Zero-Shot Foundation Models—0
Light-weight Retinal Layer Segmentation with Global ReasoningCode0
Does SAM dream of EIG? Characterizing Interactive Segmenter Performance using Expected Information Gain—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