[NIPS2018 筆記] delta encoder: an effective sample synthesis method for few shot object recognition
Δ \Delta Δ-ENCODER：一種有效的樣本合成方法，用於小樣本識別 Delta Encoder: An Effective Sample Synthesis Method for Few Shot Object Recognition 本文亮點：少數樣本，能生成1024個目標類樣本。 Abstract Δ \Delta Δ-ENCODER：學習僅基於一個或幾個示例對新類別進行分類是現代計
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相關文章
- 1. 論文閱讀筆記《∆-encoder: an effective sample synthesis method for few-shot object recognition》
- 2. 【論文理解】A Self-supervised GAN for Unsupervised Few-shot Object Recognition
- 3. Few-shot Learning for Named Entity Recognition in Medical Text筆記
- 4. 論文閱讀筆記《Learning Compositional Representations for Few-Shot Recognition》
- 5. [論文筆記]Learning Compositional Representations for Few-Shot Recognition
- 6. 《Siamese Neural Networks for One-shot Image Recognition》筆記
- 7. [FSOD][筆記]Context-Transformer: Tackling Object Confusion for Few-Shot Detection（AAAI 2020）
- 8. 論文筆記：Prototypical Networks for Few-shot Learning
- 9. Segmentation As Selective Search for Object Recognition
- 10. 【PaddlePaddle論文復現】Few-shot Video-to-Video Synthesis論文筆記