Towards End-to-end Text Spotting with Convolutional Recurrent Neural Networks閱讀筆記
1.摘要 論文提出一種統一的網絡結構模型，這種模型可以直接通過一次前向計算就可以同時實現對圖像中文本定位和識別的任務。這種網絡結構可以直接以end-to-end的方式訓練，訓練的時候只需要輸入圖像，圖像中文本的bbox，以及文本對應的標籤信息。這種end-to-end訓練的模型，可以學習到更加豐富的特徵信息。而且，這種模型所需要的時間更少，因爲在文本檢測和識別的時候，只需要計算一次圖像的特徵，這種
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相關文章
- 1. Recurrent Convolutional Neural Networks for Text Classification閱讀筆記
- 2. Recurrent Convolutional Neural Networks for Text Classification
- 3. Recurrent Neural Networks Tutorial閱讀筆記
- 4. 【閱讀筆記】《ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks》
- 5. LSTM Recurrent Neural Networks for Short Text and Sentiment Classication文章閱讀筆記
- 6. Graph Convolutional Networks for Text Classification閱讀筆記
- 7. 《Collaborative Filtering with Recurrent Neural Networks》閱讀
- 8. Convolutional Neural Networks for Sentence Classification 閱讀筆記
- 9. TextDragon: An End-to-End Framework for Arbitrary Shaped Text Spotting閱讀筆記
- 10. SRN: Towards Accurate Scene Text Recognition with Semantic Reasoning Networks ---論文閱讀筆記