Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Fei Yin"'
Publikováno v:
International Journal of Computer Vision. 128:2386-2401
Recognition of handwritten mathematical expressions (MEs) is an important problem that has wide applications in practice. Handwritten ME recognition is challenging due to the variety of writing styles and ME formats. As a result, recognizers trained
Publikováno v:
ICDAR
In contrast to machine recognizers that rely on training with large handwriting data, humans can recognize handwriting accurately on learning from few samples, and can even generalize to handwritten characters from printed samples. Simulating this ab
Publikováno v:
Pattern Recognition. 65:251-264
Handwritten Chinese text recognition based on over-segmentation and path search integrating multiple contexts has been demonstrated successful, wherein the language model (LM) and character shape models play important roles. Although back-off N-gram
Publikováno v:
Pattern Recognition. 108:107555
Multilingual handwritten text recognition is often accomplished in two cascaded steps: script identification and handwriting recognition. However, this scheme is not optimal due to error accumulation. To perform simultaneous script identification and
Publikováno v:
ICDAR
In this paper, we propose a method for simultaneous script identification and handwritten text line recognition in multi-task learning framework. Firstly, we use Separable Multi-Dimensional Long Short-Term Memory (SepMDLSTM) to encode the input text
Publikováno v:
Advances in Chinese Document and Text Processing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c07318aa9f34b63d733e58126da2a300
https://doi.org/10.1142/9789813143685_0006
https://doi.org/10.1142/9789813143685_0006
Publikováno v:
Pattern Recognition. 47:1202-1216
This paper presents an effective approach for unsupervised language model adaptation (LMA) using multiple models in offline recognition of unconstrained handwritten Chinese texts. The domain of the document to recognize is variable and usually unknow
Publikováno v:
ICPR
This paper considers using deep neural networks for handwritten Chinese character recognition (HCCR) with arbitrary position, scale, and orientations. To solve this problem, we combine the recently proposed spatial transformer network (STN) with the
Publikováno v:
Image and Vision Computing. 31:958-968
This paper proposes a method for keyword spotting in off-line Chinese handwritten documents using a contextual word model, which measures the similarity between the query word and every candidate word in the document by combining a character classifi
Publikováno v:
Pattern Recognition. 46:155-162
Recently, the Institute of Automation of Chinese Academy of Sciences (CASIA) released the unconstrained online and offline Chinese handwriting databases CASIA-OLHWDB and CASIA-HWDB, which contain isolated character samples and handwritten texts produ