Papers with Code 아카이브

Segmentation

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/MingyeXu/IAF-Net

공식 코드

Investigate Indistinguishable Points in Semantic Segmentation of 3D Point Cloud

https://github.com/MiraPurkrabek/BBoxMaskPose

공식 코드

Detection, Pose Estimation and Segmentation for Multiple Bodies: Closing the Virtuous Circle

https://github.com/MittaDhanunjaya/Master-Thesis

공식 코드

Upgraded W-Net with Attention Gates and its Application in Unsupervised 3D Liver Segmentation

https://github.com/MoeinSorkhei/glow2

공식 코드

Full-Glow: Fully conditional Glow for more realistic image generation

https://github.com/MohsenFayyaz89/STFCN

공식 코드

STFCN: Spatio-Temporal FCN for Semantic Video Segmentation

https://github.com/Morpheus3000/intrinseg

공식 코드

Joint Learning of Intrinsic Images and Semantic Segmentation

https://github.com/Moshtaf/shift-invariant-unet

공식 코드

Investigating Shift-Variance of Convolutional Neural Networks in Ultrasound Image Segmentation

https://github.com/MrD1360/deep_segmentation_vineyards_navigation

공식 코드

Deep Semantic Segmentation at the Edge for Autonomous Navigation in Vineyard Rows

https://github.com/MrGiovanni/Nested-UNet

공식 코드

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

https://github.com/MrGiovanni/UNetPlusPlus

공식 코드

UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation

https://github.com/MrGranddy/EfficientSeg

공식 코드

EfficientSeg: An Efficient Semantic Segmentation Network

https://github.com/Murtadha44/-Intracranial-Hemorrhage-Segmentation-Using-Deep-Convolutional-Model-U-Net-

공식 코드

Intracranial Hemorrhage Segmentation Using Deep Convolutional Model

https://github.com/MyeongJin-Kim/Learning-Texture-Invariant-Representation

공식 코드

Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation

https://github.com/ND-HowardGroup/SPIE-CNN-FLIM-Denoising

공식 코드

Convolutional Neural Network Denoising in Fluorescence Lifetime Imaging Microscopy (FLIM)

https://github.com/NIC-VICOROB/SUNet-architecture

공식 코드

Acute and sub-acute stroke lesion segmentation from multimodal MRI

https://github.com/NIC-VICOROB/cnn-ms-lesion-segmentation

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Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach

https://github.com/NIC-VICOROB/stroke-mri-segmentation

공식 코드

Acute and sub-acute stroke lesion segmentation from multimodal MRI

https://github.com/NIC-VICOROB/sub-cortical_segmentation

공식 코드

Automated sub-cortical brain structure segmentation combining spatial and deep convolutional features

https://github.com/NUST-Machine-Intelligence-Laboratory/SMCP

공식 코드

Semantically Meaningful Class Prototype Learning for One-Shot Image Semantic Segmentation

https://github.com/NUST-Machine-Intelligence-Laboratory/nsrom

공식 코드

Non-Salient Region Object Mining for Weakly Supervised Semantic Segmentation

https://github.com/NVIDIA/TensorRT

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EAP4EMSIG -- Enhancing Event-Driven Microscopy for Microfluidic Single-Cell Analysis

https://github.com/NYUMedML/DARTS

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DARTS: DenseUnet-based Automatic Rapid Tool for brain Segmentation

https://github.com/NZWANG/CSC-Unet

공식 코드

CSC-Unet: A Novel Convolutional Sparse Coding Strategy Based Neural Network for Semantic Segmentation

https://github.com/Na-Z/PS-2Net

공식 코드

PS^2-Net: A Locally and Globally Aware Network for Point-Based Semantic Segmentation

https://github.com/Na-Z/attMPTI

공식 코드

Few-shot 3D Point Cloud Semantic Segmentation

https://github.com/NathanUA/BASNet

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Boundary-Aware Segmentation Network for Mobile and Web Applications

https://github.com/NazirNayal8/UEM-likelihood-ratio

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A Likelihood Ratio-Based Approach to Segmenting Unknown Objects

https://github.com/Negin-Ghamsarian/AdaptNet-MICCAI2021

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LensID: A CNN-RNN-Based Framework Towards Lens Irregularity Detection in Cataract Surgery Videos

https://github.com/NesterukSergey/segmentation_image_augmentation

공식 코드

Image Augmentation for Multitask Few-Shot Learning: Agricultural Domain Use-Case

https://github.com/NeuronXJTU/CRBNet

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Ultrasound Nodule Segmentation Using Asymmetric Learning with Simple Clinical Annotation

https://github.com/Nexuslkl/Swin_MIL

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Transformer based multiple instance learning for weakly supervised histopathology image segmentation

https://github.com/Nguyendat-bit/U-net

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ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data

https://github.com/NifTK/NiftyNet

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NiftyNet: a deep-learning platform for medical imaging

https://github.com/NikooMoradi/HNTSMRG24_team_TUMOR

공식 코드

Comparative Analysis of nnUNet and MedNeXt for Head and Neck Tumor Segmentation in MRI-guided Radiotherapy

https://github.com/NoelShin/PixelPick

공식 코드

All you need are a few pixels: semantic segmentation with PixelPick

https://github.com/NoelShin/reco

공식 코드

ReCo: Retrieve and Co-segment for Zero-shot Transfer

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.