Shuye Zhang

Learn More
Natural killer (NK) cells are abundant in the liver and have been implicated in inducing hepatocellular damage in patients with chronic hepatitis B virus (HBV) infection. However, the role of NK cells in acute HBV infection remains to be elucidated. We comprehensively characterized NK cells and investigated their roles in HBV clearance and liver pathology(More)
BACKGROUND & AIMS Hepatitis C virus (HCV) is difficult to eradicate and type III interferons (IFN-λ, composed of IL-28A, IL-28B and IL-29) are novel therapeutic candidates. We hypothesized that IFN-λ have immunomodulatory effects in HCV- infected individuals. MATERIALS AND METHODS We analyzed the expression of IFN-λ and its receptor (composed of IL-10R2(More)
In this paper, we develop a novel unified framework called DeepText for text region proposal generation and text detection in natural images via a fully convolutional neural network (CNN). First, we propose the inception region proposal network (Inception-RPN) and design a set of text characteristic prior bounding boxes to achieve high word recall with only(More)
—In this paper, we present an effective method to analyze the recognition confidence of handwritten Chinese character, based on the softmax regression score of a high performance convolutional neural networks (CNN). Through careful and thorough statistics of 827,685 testing samples that randomly selected from total 8836 different classes of Chinese(More)
Maximally stable extremal regions (MSER), which is a popular method to generate character proposals/candidates, has shown superior performance in scene text detection. However, the pixel-level operation limits its capability for handling some challenging cases (e.g., multiple connected characters, separated parts of one character and non-uniform(More)
Patch-based Single-layer Unsupervised Feature Learning (SUFL) has been successfully applied in several tasks of computer vision. In the feature learning process, the key ingredient is how to learn a good feature mapping that connects patches to feature vectors. Among various feature mapping methods, the sparse filtering is easy to be implemented and(More)
—This paper proposes an end-to-end framework, namely fully convolutional recurrent network (FCRN) for handwritten Chinese text recognition (HCTR). Unlike traditional methods that rely heavily on segmentation, our FCRN is trained with online text data directly and learns to associate the pen-tip trajectory with a sequence of characters. FCRN consists of four(More)
With the rapid development of optical character recognition (OCR), font categorization becomes more and more important. This is because font information has very wide usage and researchers came to know this point recently. In this paper, we propose a new scheme for Chinese character font categorization (CCFC), which applies LBP descriptor based Chinese(More)
Chinese font recognition (CFR) has gained significant attention in recent years. However, due to the sparsity of labeled font samples and the structural complexity of Chinese characters, CFR is still a challenging task. In this paper, a DropRegion method is proposed to generate a large number of stochastic variant font samples whose local regions are(More)