H11-M107_DOC.zip
From the dataset abstract
使用特徵解偶和自適應實例歸一 化重構的域一般性分割模型，以最小化語義信息損失來解開特徵，以提升域一般性分割模型的準確度
Source: H11-M107_Domain generalization for pathology image segmentation
Additional Information
| Field | Value |
|---|---|
| Data last updated | June 3, 2024 |
| Metadata last updated | June 3, 2024 |
| Created | June 3, 2024 |
| Format | ZIP |
| License | Other (Non-Commercial) |
| Created | 11 months ago |
| Media type | application/zip |
| Size | 154,684 |
| format | ZIP |
| id | 59ec8a94-5d54-4525-b71a-abaf5fc8e7cf |
| last modified | 11 months ago |
| md5 | 5f9ddb6f3996d28be79727c327d5f779 |
| on same domain | True |
| package id | 348e4caf-a11f-48c6-ac91-b2b4d64bf740 |
| position | 1 |
| proxy url | https://scidm.nchc.org.tw/en/dataset/348e4caf-a11f-48c6-ac91-b2b4d64bf740/resource/59ec8a94-5d54-4525-b71a-abaf5fc8e7cf/nchcproxy/H11-M107_DOC.zip |
| revision id | 04f1c711-104d-45ef-be17-1227c26d7593 |
| sha256 | 27448a867d410955dc19335f3280f4604bbf3ca8f981f22c8262656ba44386ed |
| state | active |
| url type | upload |
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