Update medical-and-biological-vision-cell-microscopy.md

sections/medical-and-biological-vision-cell-microscopy.md

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 | Fair Federated Medical Image Segmentation via Client Contribution Estimation | [![GitHub Page](https://img.shields.io/badge/GitHub-Page-159957.svg)](https://github.com/NVIDIA/NVFlare/tree/main/research/fed-ce) | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Jiang_Fair_Federated_Medical_Image_Segmentation_via_Client_Contribution_Estimation_CVPR_2023_paper.pdf) <br /> [![arXiv](https://img.shields.io/badge/arXiv-2303.16520-b31b1b.svg)](http://arxiv.org/abs/2303.16520) | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/watch?v=zV4as47EWzg) |
 | Histopathology whole Slide Image Analysis with Heterogeneous Graph Representation Learning | [![GitHub](https://img.shields.io/github/stars/HKU-MedAI/WSI-HGNN?style=flat)](https://github.com/HKU-MedAI/WSI-HGNN) | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Chan_Histopathology_Whole_Slide_Image_Analysis_With_Heterogeneous_Graph_Representation_Learning_CVPR_2023_paper.pdf) <br /> [![arXiv](https://img.shields.io/badge/arXiv-2307.04189-b31b1b.svg)](https://arxiv.org/abs/2307.04189) | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/watch?v=F47ureXZ7fo) |
 | Unsupervised Contour Tracking of Live Cells by Mechanical and Cycle Consistency Losses | [![GitHub Page](https://img.shields.io/badge/GitHub-Page-159957.svg)](https://junbongjang.github.io/projects/contour-tracking/index.html) <br /> [![GitHub](https://img.shields.io/github/stars/JunbongJang/contour-tracking?style=flat)](https://github.com/JunbongJang/contour-tracking) | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Jang_Unsupervised_Contour_Tracking_of_Live_Cells_by_Mechanical_and_Cycle_CVPR_2023_paper.pdf) <br /> [![arXiv](https://img.shields.io/badge/arXiv-2303.08364-b31b1b.svg)](http://arxiv.org/abs/2303.08364) | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/watch?v=lA9lUx9mriM) |
-| Learning To Exploit the Sequence-Specific Prior Knowledge for Image Processing Pipelines Optimization | :heavy_minus_sign: | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Qin_Learning_To_Exploit_the_Sequence-Specific_Prior_Knowledge_for_Image_Processing_CVPR_2023_paper.pdf) | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/watch?v=Oh-kgpe-S_Y) |
+| Learning to Exploit the Sequence-Specific Prior Knowledge for Image Processing Pipelines Optimization | :heavy_minus_sign: | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Qin_Learning_To_Exploit_the_Sequence-Specific_Prior_Knowledge_for_Image_Processing_CVPR_2023_paper.pdf) | [![YouTube](https://img.shields.io/badge/YouTube-%23FF0000.svg?style=for-the-badge&logo=YouTube&logoColor=white)](https://www.youtube.com/watch?v=Oh-kgpe-S_Y) |
 | RepMode: Learning to Re-Parameterize Diverse Experts for Subcellular Structure Prediction <br /> ![CVPR - Highlight](https://img.shields.io/badge/CVPR-Highlight-FFFF00) | [![GitHub Page](https://img.shields.io/badge/GitHub-Page-159957.svg)](https://correr-zhou.github.io/RepMode/) <br /> [![GitHub](https://img.shields.io/github/stars/Correr-Zhou/RepMode?style=flat)](https://github.com/Correr-Zhou/RepMode) | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Zhou_RepMode_Learning_to_Re-Parameterize_Diverse_Experts_for_Subcellular_Structure_Prediction_CVPR_2023_paper.pdf) <br /> [![arXiv](https://img.shields.io/badge/arXiv-2212.10066-b31b1b.svg)](http://arxiv.org/abs/2212.10066) | :heavy_minus_sign: |
 | Towards Trustable Skin Cancer Diagnosis via Rewriting Model's Decision | :heavy_minus_sign: | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Yan_Towards_Trustable_Skin_Cancer_Diagnosis_via_Rewriting_Models_Decision_CVPR_2023_paper.pdf) <br /> [![arXiv](https://img.shields.io/badge/arXiv-2303.00885-b31b1b.svg)](https://arxiv.org/abs/2303.00885) | :heavy_minus_sign: |
 | Task-Specific Fine-Tuning via Variational Information Bottleneck for Weakly-Supervised Pathology whole Slide Image Classification | [![GitHub](https://img.shields.io/github/stars/invoker-LL/WSI-finetuning?style=flat)](https://github.com/invoker-LL/WSI-finetuning) | [![thecvf](https://img.shields.io/badge/pdf-thecvf-7395C5.svg)](https://openaccess.thecvf.com//content/CVPR2023/papers/Li_Task-Specific_Fine-Tuning_via_Variational_Information_Bottleneck_for_Weakly-Supervised_Pathology_Whole_CVPR_2023_paper.pdf) <br /> [![arXiv](https://img.shields.io/badge/arXiv-2303.08446-b31b1b.svg)](http://arxiv.org/abs/2303.08446) | :heavy_minus_sign: |