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Segmentation

Papers

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Showing 4451–4475 of 13072 papers

TitleStatusHype
Automated Measurements of Key Morphological Features of Human Embryos for IVF—0
Automated Mammogram Analysis with a Deep Learning Pipeline—0
A Labeled Array Distance Metric for Measuring Image Segmentation Quality—0
Fully-Automatic Synapse Prediction and Validation on a Large Data Set—0
Fully Convolutional Multi-scale Residual DenseNets for Cardiac Segmentation and Automated Cardiac Diagnosis using Ensemble of Classifiers—0
Fuse4Seg: Image-Level Fusion Based Multi-Modality Medical Image Segmentation—0
Cut out the annotator, keep the cutout: better segmentation with weak supervision—0
CUSUM Filter for Brain Segmentation on DSC Perfusion MR Head Scans with Abnormal Brain Anatomy—0
Automated lung segmentation from CT images of normal and COVID-19 pneumonia patients—0
Task-Specific Adaptation of Segmentation Foundation Model via Prompt Learning—0
Customizing Neural Machine Translation for Subtitling—0
A Knowledge Distillation framework for Multi-Organ Segmentation of Medaka Fish in Tomographic Image—0
A Comprehensive Review of U-Net and Its Variants: Advances and Applications in Medical Image Segmentation—0
Customize Segment Anything Model for Multi-Modal Semantic Segmentation with Mixture of LoRA Experts—0
Automated Lesion Segmentation in Whole-Body FDG-PET/CT with Multi-modality Deep Neural Networks—0
Customized SAM 2 for Referring Remote Sensing Image Segmentation—0
Customizable Architecture Search for Semantic Segmentation—0
Automated Kidney Segmentation by Mask R-CNN in T2-weighted Magnetic Resonance Imaging—0
A kinetic approach to consensus-based segmentation of biomedical images—0
Fully Automatic Myocardial Segmentation of Contrast Echocardiography Sequence Using Random Forests Guided by Shape Model—0
Customer Segmentation of Wireless Trajectory Data—0
Minimizing Labeling Effort for Tree Skeleton Segmentation using an Automated Iterative Training Methodology—0
AKGNet: Attribute Knowledge-Guided Unsupervised Lung-Infected Area Segmentation—0
CUS3D :CLIP-based Unsupervised 3D Segmentation via Object-level Denoise—0
Curvilinear object segmentation in medical images based on ODoS filter and deep learning network—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