H11-M11.zip
From the dataset abstract
Drop2Sparse為改良的 資料集蒸餾 (Dataset Distillation, DD) 方法，透過 隨機稀疏化 (random sparsification) 已訓練完成的模型，產生具多樣性與正則化效果的子網路，進而提升合成資料集的品質與泛化能力。其用途為： • 分類任務：影像分類基準（CIFAR-10/100, ImageNet-10/100） •...
Source: H11-M11_以數據蒸餾為基礎的小樣本學習方法
Additional Information
| Field | Value |
|---|---|
| Data last updated | October 31, 2025 |
| Metadata last updated | September 30, 2025 |
| Created | September 30, 2025 |
| Format | application/zip |
| License | Other (Non-Commercial) |
| created | 2 months ago |
| format | ZIP |
| id | 61b0f1f4-ac8f-48f3-9dbf-103dbc52004e |
| last modified | 1 month ago |
| md5 | 08e7da5b99392cc88eef3f0488b555dc |
| mimetype | application/zip |
| on same domain | True |
| package id | a5141548-b5ff-48dc-9cae-40b576f9aa3c |
| proxy url | https://scidm.nchc.org.tw/en/dataset/a5141548-b5ff-48dc-9cae-40b576f9aa3c/resource/61b0f1f4-ac8f-48f3-9dbf-103dbc52004e/nchcproxy/H11-M11.zip |
| revision id | 4766a328-ecb8-48dc-b0f4-407a77d5235d |
| sha256 | bb92711496aac40c7ac14b453413df6d00812895a75e3354a04790b99d2b6331 |
| size | 356.4 KiB |
| state | active |
| url type | upload |
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