21 citations · 34 across the 3 of their papers we have counts for
7 papers
Aggregation Cross-Entropy for Sequence Recognition
Zecheng Xie, Yaoxiong Huang, Yuanzhi Zhu +3
In this paper, we propose a novel method, aggregation cross-entropy (ACE), for sequence recognition from a brand new perspective. The ACE loss function exhibits competitive perform…
Tightness-aware Evaluation Protocol for Scene Text Detection
Yuliang Liu, Lianwen Jin, Zecheng Xie +3
Evaluation protocols play key role in the developmental progress of text detection methods. There are strict requirements to ensure that the evaluation methods are fair, objective…
DeRPN: Taking a further step toward more general object detection
Lele Xie, Yuliang Liu, Lianwen Jin +1
Most current detection methods have adopted anchor boxes as regression references. However, the detection performance is sensitive to the setting of the anchor boxes. A proper sett…
Fully Convolutional Recurrent Network for Handwritten Chinese Text Recognition
Zecheng Xie, Zenghui Sun, Lianwen Jin +2
This paper proposes an end-to-end framework, namely fully convolutional recurrent network (FCRN) for handwritten Chinese text recognition (HCTR). Unlike traditional methods that re…
Improved Deep Convolutional Neural Network For Online Handwritten Chinese Character Recognition using Domain-Specific Knowledge
Weixin Yang, Lianwen Jin, Zecheng Xie +1
Deep convolutional neural networks (DCNNs) have achieved great success in various computer vision and pattern recognition applications, including those for handwritten Chinese char…
DropSample: A New Training Method to Enhance Deep Convolutional Neural Networks for Large-Scale Unconstrained Handwritten Chinese Character Recognition
Weixin Yang, Lianwen Jin, Dacheng Tao +2
Inspired by the theory of Leitners learning box from the field of psychology, we propose DropSample, a new method for training deep convolutional neural networks (DCNNs), and apply…