OHW系列之一《Stroke Sequence-Dependent DCNN for Online Handwritten Chinese Character Recognition 》
文章目錄 一、論文摘要 二、論文的國內外現狀 **傳統方法流程**： 三、論文算法模型 模型概述： 模型細節： 四、論文實驗結果 五、論文創新點 六、論文鏈接 一、論文摘要 本文提出一種名爲Stroke Sequence-dependent Deep Convolutional Neural Network(SSDCNN)的模型，模型將Stroke sequence information 和八方
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相關文章
- 1. 【論文學習】Combination of ResNet and Center Loss Based Metric Learning for Handwritten Chinese Character
- 2. Glyce: Glyph-vectors for Chinese Character Representations
- 3. 《Character-Based LSTM-CRF with Radical-Level Features for Chinese Named Entity Recognition》論文解讀
- 4. GitHub & puppeteer & Chinese character & bug
- 5. 【nlp論文筆記】 Glyce: Glyph-vectors for Chinese Character Representations
- 6. BP neural network algorithm realizes handwritten numeral recognition
- 7. Deep Covariance Descriptors for Facial Expression Recognition
- 8. Usaco Training Section 5.4 Character Recognition
- 9. 論文筆記-Leverage Lexical Knowledge for Chinese Named Entity Recognition via Collaborative Graph Network
- 10. 圖片OCR（Optical Character Recognition）