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Data & Augmentations
curtis(김일두) edited this page Apr 10, 2018
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Model | Data Aug Method | Valid Loss | Valid mIOU(inference) | Score | Kaggle LB |
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Unet | Default | 0.0668 | 0.4710 | 0.4999 | 0.471 |
Unet | Transparency | 0.0636 | 0.4743 | 0.4992 | 0.472 |
Unet | Thick line | 0.0637 | 0.4722 | 0.4952 | 0.494 |
- Allen(주최측) 에서 나누어둔 이미지별 Class : https://www.kaggle.com/c/data-science-bowl-2018/discussion/48130
- ./metadata/allencls.csv
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H&E Dataset [USED]
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Harvard Crowd-Sourced Nuclei Annotation Data
- https://becklab.hms.harvard.edu/software/psb-crowdsourced-nuclei-annotation-data-1
- /data/public/rw/datasets/dsb2018/origin_ext_train_kmeans
- /data/public/rw/datasets/dsb2018/origin_ext_valid_kmeans
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TNBC Dataset
- https://www.kaggle.com/branislav1991/converting-tnbc-external-data-to-dsb2018-format/notebook
- /data/public/rw/datasets/dsb2018/extra_data_tnbc
Data Handling
Models
Ensemble
Etc