Abstract:Nowadays, people are increasingly using electronic formats to store data. In order to convert the table in paper into digital information, this project implements a handwritten Chinese character recognition system for table pictures, which releases the pressure of manual workload of typing handwritten Chinese character information. This project pre-processes the scanned images, extracts the handwritten text information from the images . Then segment the cell in the table and cuts the individual Chinese characters. In order to improve the accuracy of character cutting, this project adopts the combination of vertical projection and aspect ratio of character to determine the cutting position. The ResNext50 model is used for model training, and the two models are trained to recognize numbers, letters and handwritten Chinese characters respectively. The accuracy of the Chinese character recognition model is more than 90%, and that of the number and letter recognition model is 98%. Based on the contents filled in the table, the list of proper nouns is used to correct the recognition results and improve the accuracy. By calculating Levenshtein distance find the specific nouns with the highest similarity. The method proposed in this paper effectively complete the separation and recognition of handwritten Chinese characters in the table image.

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	1. Design and Implementation of Handwritten Chinese Characters Recognition Based on Deep Learning
	Jingyi Shen
	Computer Science and Technology 24 March 2022
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	Abstract:Nowadays, people are increasingly using electronic formats to store data. In order to convert the table in paper into digital information, this project implements a handwritten Chinese character recognition system for table pictures, which releases the pressure of manual workload of typing handwritten Chinese character information. This project pre-processes the scanned images, extracts the handwritten text information from the images . Then segment the cell in the table and cuts the individual Chinese characters. In order to improve the accuracy of character cutting, this project adopts the combination of vertical projection and aspect ratio of character to determine the cutting position. The ResNext50 model is used for model training, and the two models are trained to recognize numbers, letters and handwritten Chinese characters respectively. The accuracy of the Chinese character recognition model is more than 90%, and that of the number and letter recognition model is 98%. Based on the contents filled in the table, the list of proper nouns is used to correct the recognition results and improve the accuracy. By calculating Levenshtein distance find the specific nouns with the highest similarity. The method proposed in this paper effectively complete the separation and recognition of handwritten Chinese characters in the table image.
	TO cite this article:Jingyi Shen. Design and Implementation of Handwritten Chinese Characters Recognition Based on Deep Learning[OL].[24 March 2022] http://en.paper.edu.cn/en_releasepaper/content/4756976


	2. Compressive Hyperspectral Video Reconstruction Via Multitask Nonparametric Bayesian Learning
	Yang Man,Gao Zhanchun
	Computer Science and Technology 09 February 2022
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	Abstract:Compressive hyperspectral video reconstruction (CHVR) extends snapshot spectral imaging into the temporal dimension, which allows fast hyerspectral observation of dynamic scenes. This paper proposes a multitask learning method for CHVR under the blind compressive sensing framework, characterized by joint inference of the representation atoms and the corresponding coefficients, directly from the compressive measurements. Defining the compressive reconstruction of each frame as a single task, our method employs a common dictionary shared by all tasks, which significantly alleviates the data paucity problem. The complete inference process is fulfilled via a Bayesian nonparametric estimation strategy, which contributes three advantages: reliable generalizability, parameter-tuning free and automatic determination of the model complexity. Simulation results demonstrate the efficacy of the proposed approach.
	TO cite this article:Yang Man,Gao Zhanchun. Compressive Hyperspectral Video Reconstruction Via Multitask Nonparametric Bayesian Learning[OL].[ 9 February 2022] http://en.paper.edu.cn/en_releasepaper/content/4756225

Saved Papers

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	3. A generality enhanced forensic towards GAN facial images
	Xiong Xiao-Fang,Yang Gao-Bo
	Computer Science and Technology 13 May 2020
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	Abstract:\justifying Recent advances in GAN technique have made it much easier than ever to generate believable face images, which brings some potential security issues to the public. Currently a variety of architectures have been proposed to detect these generated fake images, but few works address the problem of generalization ability of forensics models, which means most of them need prior knowledge of the structure of GAN model when detecting a specific GAN fake face images, and unable to detect unseen fake images generated by other GAN models. In this work, we tackle the generality enhanced problem by adding a fixed weight convolutional layer before CNN structure, which contain three designed high-pass filters. Firstly, we convert RGB images to YCbCr color space to get more obvious edge information. Then, EfficientNet is adopted as our basic CNN structure to extract inhenrent features and classify them. Finally, a fixed weight layer is added to the first convolutional layer, which could greatly suppress the semantic image content and magnify microscopic characteristics of images, thus help to enhance the generalization ability of the model. A series of experiments demonstrate that our approach achieve superior performance compare with the state-of-the-art work in terms of the generality of forensics model.
	TO cite this article:Xiong Xiao-Fang,Yang Gao-Bo. A generality enhanced forensic towards GAN facial images[OL].[13 May 2020] http://en.paper.edu.cn/en_releasepaper/content/4752048


	4. Super-resolution Reconstruction of Mosaic Face Images Based on GAN
	Xu Yonghui,Yang Gaobo
	Computer Science and Technology 11 May 2020
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	Abstract:With the rapid development of artificial intelligence technologies, image super-resolution which is one of the hottest topics in computer vision community, has achieved attractive progresses. To restore mosaic face images, we present an effective model, namely DemosaicGAN. It combines existing SRGAN and RDN and optimizes the perceptual loss functions. As far as we concerned, our experimental results show that the proposed DemosaicGAN achieves the best results in super-resolution reconstruction of mosaic face images so far.
	TO cite this article:Xu Yonghui,Yang Gaobo. Super-resolution Reconstruction of Mosaic Face Images Based on GAN[OL].[11 May 2020] http://en.paper.edu.cn/en_releasepaper/content/4752050


	5. Class-balanced and Local Median Loss Jointly Supervised for Wild Facial Expression Recognition
	Shi Cong-Cong,TIAN,TIAN Mei
	Computer Science and Technology 07 February 2020
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	Abstract:Over the past few years, Convolutional Neural Networks (CNNs) have shown effective performance on facial expression recognition. However, it is still a challenge problem for facial expression in the wild. The facial expression recognition dataset in the wild usually has the problem that imbalanced distribution of facial expression data and large intra-class differences caused by factors such as pose, lighting and gender. In order to solve this problem, this paper presents a novel loss function -- CALM Loss (Class-balanced and Local Median Loss). CALM Loss contains two parts. The first part is the class-balanced softmax loss function, which is uesd to solve the problem of data imbalance. The data set is divided into two classes, with two expressions with less data as one class and the other five as one class. During the network training process, the weight of the class with less data is adaptively increased. The second part is the local median loss function, which uses the median of serveral neatest neighbors in the same class as the center of class, weakens the influence of difficult samples on the selection of class center. Finally, the CALM Loss training network was adopted in this paper. The average recognition accuracy on the RAF dataset reaches 77.34$\%$, which proves the effectiveness of the proposed method.
	TO cite this article:Shi Cong-Cong,TIAN,TIAN Mei. Class-balanced and Local Median Loss Jointly Supervised for Wild Facial Expression Recognition[OL].[ 7 February 2020] http://en.paper.edu.cn/en_releasepaper/content/4750634


	6. A Telecom Anti-Fraud Approach Based on Graph
	Li Zhengzheng,Wang Chun
	Computer Science and Technology 05 February 2020
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	Abstract:Currently, telecommunications fraud is on the rise. Traditional anti-fraud techniques are basically unable to capture various new telecommunication fraud methods. After studying the case of fraud, we proposes a telecom fraud detection method based on graph embedding, which is used to mine the potential features of the call correlation graph between fraudsters and users. First, the proposed approach is based on the embedding of attribute network, which not only saves the network structure information, but also incorporates the statistical features of the nodes extracted for the call behavior, in order to represent the nodes as low-dimensional vectors. Secondly, the proposed approach belongs to semi-supervised learning. In the supervised part, the corresponding labels are predicted. In the unsupervised part, the node context vector is predicted. Both share parameters and optimize the model at the same time. When experimenting on the telecommunications fraud dataset, compared with other baseline approaches., the experimental results prove the effectiveness of the proposed method in countering telecommunications fraud.
	TO cite this article:Li Zhengzheng,Wang Chun. A Telecom Anti-Fraud Approach Based on Graph[OL].[ 5 February 2020] http://en.paper.edu.cn/en_releasepaper/content/4750616


	7. Integrating Ecological Effects Assessment and Scenario-Based Simulation to Optimize Spatial Management Decisions: a Case Study of Three Gorges Reservoir Area
	LIU Minghao,FENG Yuan,YUAN Min,LI Yuting
	Computer Science and Technology 14 May 2018
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	Abstract:It is of great significance to promote the sustainable development of land by revealing the spatial temporal evolution law of land use and land cover change (LUCC), and identifying the ecological security. Three different development scenarios (low speed development, inertia development, rapid development) of the Three Gorges Reservoir Area（TGR）are designed based on the dynamic change model of urban and rural land use by using DYNA-CLUE software to simulate the spatial distribution pattern of land use in TGR, along with the human affect index (HAI), ecological risk index (ERI) and ecosystem service value (ESV) are used to assess the ecological effects of the different development scenarios. Results shows that, (1) the ROC test values of the logistic regression model between driving factors and grassland, cultivated land, shrub land, forest land, wetland, water body and artificial surface respectively were 0.61, 0.647, 0.819, 0.987, 0.777, 0.935, 0.927; (2) the land use distribution was simulated from 2000 to 2010, and the model validation shows that the total kappa reaches 79%, comparing the simulation results with the land use status in 2010;（3）From the ecological effect evaluation, the scenarioⅠis the best, the scenarioⅡ is the worst, and the scenario III is between the scenarioⅠand the scenarioⅡ;（4）from the perspective of time , ecological risk presents a gradual shift trend of from low to medium and high risk with the passage of time; from the perspective of space, relatively strong ecological risk areas are mainly concentrated in the riparian zone along the Yangtze River west of Wanzhou, while the extremely strong ecological risk area are mainly concentrated in the urbanized area of Chongqing metropolitan area.
	TO cite this article:LIU Minghao,FENG Yuan,YUAN Min, et al. Integrating Ecological Effects Assessment and Scenario-Based Simulation to Optimize Spatial Management Decisions: a Case Study of Three Gorges Reservoir Area[OL].[14 May 2018] http://en.paper.edu.cn/en_releasepaper/content/4744748


	8. A User Interest Recommendation Model Based on Topic Network and Social Graph
	TANG Zhirong,TIAN Ye,WANG Wendong
	Computer Science and Technology 02 May 2017
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	Abstract:Detecting user interested topics is one of the most important issues in a recommender system. A topic recommendation model is proposed in this paper, which utilizes the topic network and the social graph to recommend topics that are interesting to the user. The model could be applied to a social Q&A (Question and Answering) system. First, all the topics in the social Q&A system are organized as a topic network. By analyzing the topics that the users have followed and the topic distribution in the topic network, we explore the most relevant topics for users. Secondly, we observe that the topics which attract the majority of our friends or the topics that our best friends are concerned about, might be prospective interesting topics for us. Therefore, we consider these two kinds of scenarios simultaneously to design the topic recommendation algorithm. Based on the data set derived from the Quora website, the experimental results demonstrate that our algorithm outperforms the standard Collaborative Filtering (CF) in the accuracy.
	TO cite this article:TANG Zhirong,TIAN Ye,WANG Wendong. A User Interest Recommendation Model Based on Topic Network and Social Graph[OL].[ 2 May 2017] http://en.paper.edu.cn/en_releasepaper/content/4731619


	9. Adaptive Clustering Algorithm based small Group Detection and Tracking
	CHENG Zhongbin,ZOU Qi,TIAN Mei
	Computer Science and Technology 02 September 2016
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	Abstract:We propose to detect and track small groups of individuals who are traveling together in surveiuance videos. Coherent groups are dynamically updated through merge and split events. To handle these challenges, we propose to discover groups by adaptive clustering (AGD). Experiments on challenging videos (FM dataset) which have complex motions and occlusions show that the proposed method based on trajectory-level similarity can correctly discover dynamic changes of groups. The effectiveness of the proposed approach is shown through comparison with classical methods.
	TO cite this article:CHENG Zhongbin,ZOU Qi,TIAN Mei. Adaptive Clustering Algorithm based small Group Detection and Tracking[OL].[ 2 September 2016] http://en.paper.edu.cn/en_releasepaper/content/4703372


	10. Procedural Texture Generation Based on Semantic Descriptions
	DONG Jun-Yu, WANG Li-Na, LIU Jun,SUN Xin
	Computer Science and Technology 10 May 2016
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	Abstract:Procedural textures are normally generated from mathematical models and have been widely used in computer games and animations for efficient rendering of natural elements, such as wood, marble, stone and other materials. Although the intuitive way to describe procedural texture is to use semantic attributes, there is no connection between procedural models, model parameters and texture semantic descriptions. In this paper, we propose a novel framework for generating procedural textures according to semantic descriptions. First a vocabulary of semantic attributes is collected for describing procedural textures based on extensive psychophysical experiments. Then a multi-label learning method is employed to label more new textures using the semantic attributes. We construct a procedural texture dataset with semantic attributes and further learn a low-dimensional semantic texture space. Finally, for a set of input semantic descriptions, we are able to find a generation model with proper parameters in this space. This model can be used to generate procedural textures that retain the input semantic attributes. Experimental results show that the proposed framework is effective and the generated procedural textures are correlated with the corresponding input semantic descriptions.
	TO cite this article:DONG Jun-Yu, WANG Li-Na, LIU Jun, et al. Procedural Texture Generation Based on Semantic Descriptions[OL].[10 May 2016] http://en.paper.edu.cn/en_releasepaper/content/4688895

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