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	1. A Topic Detection Algorithm Based on Multiple Strategies for Group Chat
	Wu Xu,Chen Chunxu
	Computer Science and Technology 22 February 2021
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (416K B)

	Abstract:There are a large number of group chat messages on the Internet, and public opinion analysis requires topic detection to aggregate messages with similar discussions. Group chat topics are easy to be crossing and parallel, and group chat messages also have the characteristics of sparse text features. In order to solve these two problems, this paper proposes a multi-strategy group chat topic detection technology. On the one hand, the topic sequence is constructed to solve the problem of topic crossing and parallel, on the other hand, the user, time, type and other attributes of the message are used to make up for the shortcomings of clustering that rely solely on short text features. The results of experiments conducted on three datasets derived from real group chat logs show that this method has better performance than traditional algorithms. In addition, the types of group chat messages it can process are much more than traditional methods.
	TO cite this article:Wu Xu,Chen Chunxu. A Topic Detection Algorithm Based on Multiple Strategies for Group Chat[OL].[22 February 2021] http://en.paper.edu.cn/en_releasepaper/content/4753717


	2. Head Pose Estimation Based on Dlib and Savitzky-Golay Smoothing Algorithm
	LU Xiaoning,LIU Wen
	Computer Science and Technology 18 January 2021
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (347K B)

	Abstract:In this paper, We apply the Savitsky-Golay filter algorithm to head pose estimation. Firstly, the Dlib algorithm is to detect key points of the corresponding face in the video. Then, the function solvepnp built in opencv is to estimate the pose. Finally, through MATLAB simulation, we can find that the Savitsky-Golay filter algorithm can filter the noisiness in the observed data to obtain a smoother and more accurate change trajectory of head pose.
	TO cite this article:LU Xiaoning,LIU Wen. Head Pose Estimation Based on Dlib and Savitzky-Golay Smoothing Algorithm[OL].[18 January 2021] http://en.paper.edu.cn/en_releasepaper/content/4753447


	3. Risk Quantification Contributes To Service Stability
	Liu Funiu
	Computer Science and Technology 07 August 2020
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (572K B)

	Abstract:This article shows the design and implementation of a system called risk quantification platform. On the whole, the risk quantification platform is designed to standardize the changes in the product line from the perspective of prevention. We use the quantified data to conduct a risk assessment and combine the case improvement module to drive the business side to optimize the stability of online services, achieving the goal of reducing the occurrence of the online cases. By automatically collecting user platform operation and maintenance data, and automatically calculating and quantifying the operation and maintenance risks, each bussiness line gets risk scores of various dimentions. Finally, a ranking and competition mechanism is formed to achieve the purpose of promoting long-term implementation of standards and assisting in the construction of service stability.
	TO cite this article:Liu Funiu. Risk Quantification Contributes To Service Stability[OL].[ 7 August 2020] http://en.paper.edu.cn/en_releasepaper/content/4752636


	4. MobiPDF: Reconstructing PDF contents for Mobile Devices
	Peng Jin,Ligang He,Yilian Zhou,Cheng Chang,Liangtang Lei,Xiaorui Zhang,Hao Chen
	Computer Science and Technology 22 May 2020
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (1297K B)

	Abstract:The PDF format is widely used in academia with its elegant style and unmodifiable features. With the popularity of mobile terminals, more and more people use mobile devices to browse and obtain documents. However, once the PDF document is generated, the style is fixed. It is difficult to read on a small-sized mobile screen. In this work, we develop a system called MobiPDF to reconstruct the content in a PDF document and render it in a way so that it can viewed properly on a mobile screen. In particular, the content of the PDF document is first decomposed into different areas. The PDF file is then converted into an HTML format file and also to an image file. Next, the texts and their rendering information are extracted from the HTML file according to the positions of the decomposed areas. In addition, the non-text information such as figures and tables is extracted from the image file based on its positions. The extracted text and non-text contents together with the rendering information are reconstructed as a new HTML file according to the size of the user\'s mobile screen. We have developed MobiPDF as a web service, which is hosted on the Tencent Cloud and can be accessed publically.
	TO cite this article:Peng Jin,Ligang He,Yilian Zhou, et al. MobiPDF: Reconstructing PDF contents for Mobile Devices[OL].[22 May 2020] http://en.paper.edu.cn/en_releasepaper/content/4752113


	5. A generality enhanced forensic towards GAN facial images
	Xiong Xiao-Fang,Yang Gao-Bo
	Computer Science and Technology 13 May 2020
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (563K B)

	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


	6. Super-resolution Reconstruction of Mosaic Face Images Based on GAN
	Xu Yonghui,Yang Gaobo
	Computer Science and Technology 11 May 2020
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (899K B)

	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


	7. Image completion algorithm based on label differentiation
	Ye Zixiao, Tan Guanghua
	Computer Science and Technology 29 April 2020
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (1343K B)

	Abstract:Image completion is an important research direction in computer vision and has broad application prospects. Deep learning based image completion methods are generally based on three technologies, namely the autoencoder-based method, the generation of adversarial networks based method and the recurrent network based method. However, the output results of most methods are very single, for each masked Image input can only generate one completion result. Because the probability space corresponding to the possible results of each defective image is very large, in order to obtain the diversity of the completion results, this paper proposes an image completion method based on label differentiation, called LD-PICNet (Label Differentiation PICNet) This method can not only generate a complete image with clear and good semantic information, but also actively edit the tags on the generated results to maximize the diversity of the output. Specifically, this paper introduces an auxiliary classifier similar to ACGAN, which uses a single label of the image ground truth to reconstruct the image, and uses the label to actively increase the difference of the latent vectors during image completion to achieve variability of output. In addition, this paper also introduces a depth-weighted loss function through information entropy. The deeper the position of the image masked area, the lower the weight is given to further enhance the ability of the model to diversify the output&#

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