論文《Fast and Accurate Entity Recognition with Iterated Dilated Convolutions》
論文地址：Fast and Accurate Entity Recognition with Iterated Dilated Convolutions 對於序列標註問題，普通的CNN有一個劣勢：卷積之後，末層神經元可能只是得到了原始輸入數據中一小塊的信息。而對於命名實體識別，整個句子的每個字對當前需要標註的字產生影響。爲了覆蓋更多的信息，加入更多的卷積層，這樣會導致層數越來越深，參數越來越多，爲
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相關文章
- 1. Fast and Accurate Recognition of Chinese Clinical Named Entities with Residual Dilated Convolutions
- 2. 論文Fast and accurate short read alignment with Burrows-Wheeler transform
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- 4. 論文閱讀：Dilated Convolutions with Lateral Inhibitions for Semantic Image Segmentation
- 5. Semantic Flow for Fast and Accurate Scene Parsing
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- 7. 《Receptive Field Block Net for Accurate and Fast Object Detection》論文筆記
- 8. 論文SDP + RCNN | Exploit All the Layers: Fast and Accurate CNN Object Detector with SDP and CRC
- 9. Receptive Field Block Net for Accurate and Fast Object Detection論文筆記
- 10. 【論文筆記】A Unified MRC Framework for Named Entity Recognition