| 1. | The continuous handwriting chinese characters recognition is the trend of handwriting chinese recognition
联机连续手写体字符识别是手写体识别的发展趋势。 |
| 2. | The result of the experiment show that the raising one ' s hand arithmetic can improve the capability of the handwritten numeral recognition system
实验结果表明，举手表决组合算法法能够提高手写体识别系统的性能。 |
| 3. | After nearly 200 years development , pitman ' s shorthand is now a very robust shorthand recording system , and it ' s the most popular shorthand in the english world
旨在通过对英文pitman速记手写体识别的研究，探求出一条计算机人机告诉信息交互的方法。 |
| 4. | With the popular ‘ kernel method ’ in machine learning and the extensively - existed ‘ small - world networks ’ in society , we propose the corresponding imrpoved am models , and apply them to face recogntion and handwriting recogntion
借助机器学习领域中流行的核技巧和现实社会中普遍存在的小世界网络,提出了相应的am改进模型,并将其应用于人脸识别、手写体识别问题。 |
| 5. | By this time , the rate of single handwritten character recognition , especially figure recognition , has reached 95 % . but to the sequential characters , or mathematic character recognition there is not a perfect product
到现在，单字符手写体识别，尤其是数字识别率接近95 ，但对于连续的字符书写，尤其是有数学符号的情况下，由于联机手写的随意性比较大，写作不规范，还没有一个成熟的产品。 |
| 6. | Because only the handwritten character on the form is need to be processed , this paper put forward a automatic geometric structure learning method based on the typographic and handwritten text recognition ( thr ) to find out the handwritten area
由于表格文档中需要处理的信息大多数是人工填写的字符，本文提出了基于印刷体与手写体识别的表格几何结构自动学习方法。通过手写体与印刷体识别，自动确定手写体区域的位置和大小。 |
| 7. | It has been applied to a lot of areas and become one active research subject on computer vision and pattern recognition . many researchers have studied the online handwriting identification . however , the offline handwriting identification is seldom explored in that the latter is much more difficult than the former
不少学者对在线手写体识别作了很多研究工作，而关于离线手写体笔迹鉴别的文献则要少得多，这一方面是由于手写体识别本身的复杂性；另一方面，离线手写体笔迹鉴别要比在线鉴别困难得多。 |
| 8. | Their input capabilities are limited to a few buttons or numbers , or entering data takes extra time , as happens with a personal digital assistant ' s ( pda ) handwriting - recognition capabilities . they have less processing power and memory to work with , and their wireless network connections have less bandwidth and are slower than those of computers hard - wired to fast lans
它们的输入功能局限于几个按键或数字键，或者像个人数字助理（ pda ）手写体识别功能那样，输入数据要花很长时间，它们所拥有的工作处理能力和内存都较校比起那些通过计算机硬连线与快速局域网相连的连接，它们的无线网络连接带宽较窄，速度也较慢。 |
| 9. | Many research topics had focused on how human can input information into a computer as quickly as possible with high accuracy rate in an easy way . the recognition of handwritten word is one possible solution . but the recognition of nature word writings encountered lots of problems , such as , low writing speed and low recognition rate
手写体识别的研究为解决这个问题提供了一个必要的条件，但是由于传统文字的特点，使得识别的正确率很难取得突破性的进展，而且传统文字记录的缓慢速度也制约了它作为高速录入的解决方案的可能。 |
