H11-M11_code.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 | October 31, 2025 |
| Created | October 31, 2025 |
| Format | application/zip |
| License | Other (Non-Commercial) |
| created | 1 month ago |
| format | ZIP |
| id | aab834d4-f1cb-4931-9325-ed088db339f0 |
| last modified | 1 month ago |
| md5 | 232cef47c9a3140f5dae874e3890391d |
| mimetype | application/zip |
| on same domain | True |
| package id | a5141548-b5ff-48dc-9cae-40b576f9aa3c |
| position | 1 |
| proxy url | https://scidm.nchc.org.tw/en/dataset/a5141548-b5ff-48dc-9cae-40b576f9aa3c/resource/aab834d4-f1cb-4931-9325-ed088db339f0/nchcproxy/H11-M11_code.zip |
| revision id | 7483c6b3-603f-4717-872e-0bbe5e20edee |
| sha256 | 1e79284eb4b1112c43348706f09b9644255fe8f7bb93cf5233ab34d155472487 |
| size | 136.4 KiB |
| state | active |
| url type | upload |
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