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Segmentation

Papers

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Showing 6551–6575 of 13072 papers

TitleStatusHype
Adversarial Neural Networks in Medical Imaging Advancements and Challenges in Semantic Segmentation—0
Frequency Disentangled Learning for Segmentation of Midbrain Structures from Quantitative Susceptibility Mapping Data—0
Decomposition-based Unsupervised Domain Adaptation for Remote Sensing Image Semantic Segmentation—0
A Review on Automatic License Plate Recognition System—0
Deep-ASPECTS: A Segmentation-Assisted Model for Stroke Severity Measurement—0
Frequency and Spatial domain based Saliency for Pigmented Skin Lesion Segmentation—0
Deep asymmetric mixture model for unsupervised cell segmentation—0
CLIP-S4: Language-Guided Self-Supervised Semantic Segmentation—0
Freeze the backbones: A Parameter-Efficient Contrastive Approach to Robust Medical Vision-Language Pre-training—0
A Review on Automated Brain Tumor Detection and Segmentation from MRI of Brain—0
Latent Anomaly Detection: Masked VQ-GAN for Unsupervised Segmentation in Medical CBCT—0
Latent Correlation Representation Learning for Brain Tumor Segmentation with Missing MRI Modalities—0
Accelerating Diffusion Models via Pre-segmentation Diffusion Sampling for Medical Image Segmentation—0
LMSeg: A deep graph message-passing network for efficient and accurate semantic segmentation of large-scale 3D landscape meshes—0
Automatic Deep Learning System for COVID-19 Infection Quantification in chest CT—0
Latents2Segments: Disentangling the Latent Space of Generative Models for Semantic Segmentation of Face Images—0
LMSeg: Language-guided Multi-dataset Segmentation—0
Locally Adaptive Learning Loss for Semantic Image Segmentation—0
Deepbet: Fast brain extraction of T1-weighted MRI using Convolutional Neural Networks—0
Automatic defect segmentation by unsupervised anomaly learning—0
Freestyle Sketch-in-the-Loop Image Segmentation—0
LATUP-Net: A Lightweight 3D Attention U-Net with Parallel Convolutions for Brain Tumor Segmentation—0
CLIP-S^4: Language-Guided Self-Supervised Semantic Segmentation—0
Deep Cerebellar Nuclei Segmentation via Semi-Supervised Deep Context-Aware Learning from 7T Diffusion MRI—0
FreeSeg: Unified, Universal and Open-Vocabulary Image Segmentation—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