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Segmentation

Papers

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Showing 6176–6200 of 13072 papers

TitleStatusHype
FS-Net: Full Scale Network and Adaptive Threshold for Improving Extraction of Micro-Retinal Vessel Structures—0
FSNet: A Failure Detection Framework for Semantic Segmentation—0
Frustration Level Annotation in Latvian Tweets with Non-Lexical Means of Expression—0
Access Control Using Spatially Invariant Permutation of Feature Maps for Semantic Segmentation Models—0
Frustratingly Simple but Effective Zero-shot Detection and Segmentation: Analysis and a Strong Baseline—0
Fruit Detection, Segmentation and 3D Visualisation of Environments in Apple Orchards—0
A Comprehensive Approach to Diagnosing Temporomandibular Joint Diseases: AI-driven TMD Diagnostic System—0
Clustering Approach Towards Image Segmentation: An Analytical Study—0
Adversarial-Prediction Guided Multi-task Adaptation for Semantic Segmentation of Electron Microscopy Images—0
Interactive segmentation of medical images through fully convolutional neural networks—0
Interactive Segmentation of Radiance Fields—0
Interactive Segmentation on RGBD Images via Cue Selection—0
Interactive segmentation using U-Net with weight map and dynamic user interactions—0
Interactive Segmentation via Deep Learning and B-Spline Explicit Active Surfaces—0
Interactive Video Object Segmentation in the Wild—0
Learning color space adaptation from synthetic to real images of cirrus clouds—0
From Variability To Accuracy: Conditional Bernoulli Diffusion Models with Consensus-Driven Correction for Thin Structure Segmentation—0
[CLS] Token is All You Need for Zero-Shot Semantic Segmentation—0
From Text Segmentation to Smart Chaptering: A Novel Benchmark for Structuring Video Transcriptions—0
Argumentative Segmentation Enhancement for Legal Summarization—0
Access Control of Semantic Segmentation Models Using Encrypted Feature Maps—0
Learning Common and Specific Features for RGB-D Semantic Segmentation with Deconvolutional Networks—0
Automated Detection of Regions of Interest for Brain Perfusion MR Images—0
From Sparse to Precise: A Practical Editing Approach for Intracardiac Echocardiography Segmentation—0
CLR-GAM: Contrastive Point Cloud Learning with Guided Augmentation and Feature Mapping—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