Papers with Code 아카이브

Nuclear Segmentation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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평가표

1

보존된 평가 기록

4

코드

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

https://github.com/fmi-basel/RDCNet

공식 코드

RDCNet: Instance segmentation with a minimalist recurrent residual network

https://github.com/kaiko-ai/eva

공식 코드

Towards Large-Scale Training of Pathology Foundation Models

https://github.com/kaiko-ai/towards_large_pathology_fms

공식 코드

Towards Large-Scale Training of Pathology Foundation Models

https://github.com/lihaoliu-cambridge/simultaneous_semantic_and_instance_segmentation

공식 코드

Simultaneous Semantic and Instance Segmentation for Colon Nuclei Identification and Counting

https://github.com/simongraham/dsf-cnn

공식 코드

Dense Steerable Filter CNNs for Exploiting Rotational Symmetry in Histology Images

https://github.com/srijay-lab/synclay-framework

공식 코드

SynCLay: Interactive Synthesis of Histology Images from Bespoke Cellular Layouts

https://github.com/tissueimageanalytics/conic

공식 코드

CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

https://github.com/undercutspiky/sfl

공식 코드

Are nuclear masks all you need for improved out-of-domain generalisation? A closer look at cancer classification in histopathology

https://github.com/vqdang/hover_net

공식 코드

HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Images

https://github.com/vqdang/xy_net

공식 코드

HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Images

https://github.com/01pooja10/Sketch-to-Shoe

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/2023-MindSpore-1/ms-code-207

Mask R-CNN

https://github.com/2023-MindSpore-1/ms-code-208

Mask R-CNN

https://github.com/2023-MindSpore-1/ms-code-215/tree/main/Pix2Pix

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/2023-MindSpore-1/ms-code-217/tree/main/tinydarknet

Mask R-CNN

https://github.com/2023-MindSpore-1/ms-code-6/tree/main/Pix2PixHD

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/2023-MindSpore-1/ms-code-7/tree/main/tinydarknet

Mask R-CNN

https://github.com/2023-MindSpore-4/Code10/tree/main/MaskRCNN

Mask R-CNN

https://github.com/2023-MindSpore-4/Code9/tree/main/MaskRCNN

Mask R-CNN

https://github.com/AKASH2907/bird-species-classification

Mask R-CNN

https://github.com/AKASH2907/bird_species_classification

Mask R-CNN

https://github.com/AbhinavTalari/Night2Day

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/Adi-iitd/AI-Art

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/Akella17/Voice_Style_Transfer

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

https://github.com/Alexander-Whelan/Zeus

Mask R-CNN

https://github.com/Alighasemzadeh83/Pix2Pix-implementation-from-scratch

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/Alina9/Style-transfer

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

https://github.com/AlliBalliBaba/PixFace

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/AlliBalliBaba/PixFace-Neural-Network

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/AloneGu/keras_tf_neural_img

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

https://github.com/Apogentus/style-transfer-with-strength-control

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

https://github.com/AquibPy/Cycle-GAN

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/AquibPy/Pix2Pix-Conditional-GANs

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/ArenGolazizian/Pix2Pix-Cityscapes-Seg2Real

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/Arthur-Shi/py-faster-rcnn

Mask R-CNN

https://github.com/AshishSingh2261/Pedestrian_Instance_Segmentation

Mask R-CNN

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