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	1. Fusion algorithm of infrared and visible images based on LatLRR and image pyramid
	LI Ning,LI Liqun
	Computer Science and Technology 23 March 2022
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	Abstract:Aiming at the loss of high-frequency information components of visible light and infrared images fused by Latent Low-Rank Representation (LatLRR) algorithm, this paper proposes a multi-level image fusion algorithm based on the combination of LatLRR and Gauss-Laplace Pyramid. Firstly, the image is decomposed into Gaussian pyramid and Laplace pyramid, then the highest level image of Gaussian pyramid and each layer image of Laplace pyramid are decomposed into low-rank part and Significant part, meanwhile the low-rank part and significant part of infrared and visible image pyramid are blended, then the fused low-rank part and significant part are fused at all levels, and finally the image is restored by Gaussian-Laplace pyramid. The algorithm has been tested on the public data set, this method retains more high-frequency information components compared with LatLRR algorithm.
	TO cite this article:LI Ning,LI Liqun. Fusion algorithm of infrared and visible images based on LatLRR and image pyramid[OL].[23 March 2022] http://en.paper.edu.cn/en_releasepaper/content/4757034


	2. WeSSRD: A weakly supervised app store spam reviews detection framework
	LI Siyi,XU Guosheng,LIN Yan,Guo yanhui,Xu Guoai
	Computer Science and Technology 23 February 2022
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	Abstract:With the popularity of smartphones, a large number of apps have emerged in app store for users to download.Most app stores allow users who download an app to post reviews and ratings on this app. These reviews are not only a major factor in determining the ranking of an app, but also a major reference for users in choosing whether to download the app, and an important way for developers to get feedback from users.However, a large number of meaningless reviews (or called spam reviews) have severely damaged the normal ecology of the app store and are one of the urgent problems to be solved in maintaining the regular order of the mobile app market. This paper proposes a weakly supervised spam detection framework called WeSSRD. It can mine app reviews for relevance to the app itself by unsupervised topic modeling methods and then train a weakly supervised detector to detect spam in application stores using a minimal amount of prior knowledge.We tested this framework on a real dataset with 14,052 reviews. The detector trained by our proposed framework can achieve a precision rate of 80.97% and a recall rate of 81.89% on the test set, far exceeding the detection method based on similarity.
	TO cite this article:LI Siyi,XU Guosheng,LIN Yan, et al. WeSSRD: A weakly supervised app store spam reviews detection framework[OL].[23 February 2022] http://en.paper.edu.cn/en_releasepaper/content/4756424

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	3. THMobile : An Improved Network For Garbage Classification Based on MobileNet
	Zhou Jialan,Bian Jiali
	Computer Science and Technology 22 February 2022
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	Abstract:With the rapid development of deep learning, more and more image recognition models are applied to daily life. For the current neural network model, the recognition accuracy of large model is higher and higher, but the more resources are needed. The lightweight of neural network model is more conducive to the application in life. In this paper, a THMobile model with smaller size and higher accuracy is proposed based on MobileNet. On the self-made garbage dataset, the classification accuracy of it reaches 91.2%, obtaining better performance than MobileNet. And it also performs better on CIFAR-10 than MobileNet.
	TO cite this article:Zhou Jialan,Bian Jiali. THMobile : An Improved Network For Garbage Classification Based on MobileNet[OL].[22 February 2022] http://en.paper.edu.cn/en_releasepaper/content/4756338


	4. Design and Implementation of Big Data Processing Platform Based on SCA and Spark
	Zhou Yongjiang,Zhang Yang
	Computer Science and Technology 27 December 2016
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	Abstract:With the rapid development of computer technology, electronic information technology and network technology, the traditional data processing method based on web service has become difficult to meet the demand of big data. On the other hand, big data software needs to be reconstructed, They can`t reuse the existing business logic. Apache Spark is an open source cluster computing technology specifically designed for large scale data processing. Tuscany is a framework of SCA. The paper introduces a system to combine Spark and Tuscany to calculate the complex logic fleetly. At the same time, the system provide a friendly user interface to data analysis.
	TO cite this article:Zhou Yongjiang,Zhang Yang. Design and Implementation of Big Data Processing Platform Based on SCA and Spark[OL].[27 December 2016] http://en.paper.edu.cn/en_releasepaper/content/4713662


	5. The Research of Active Contour Optimization Model Based on Fast Marching Algorithm
	Liu Changzheng,Guo Junfei,Xu Lei
	Computer Science and Technology 16 January 2015
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	Abstract:The Active Contour Model is one of the mainstreams of medical image segmentation method. During the image segmentation method of the Active Contour Model, the iteration needs to calculate each pixel in the image, which leads to large amount of calculation and the slow segmentation speed, so could not reach the requirements of real-time clinical operation. In this paper, we take the simple and quick advantages of the Fast Marching to conduct the simulation experiment of optimization model on ITK platform finally. The analysis of experimental results: the optimization model can keep the smoothness of the boundary, make the common anatomical and topology structure in the medical images to process well, the complexity of the algorithm to reduce, and the robustness of the algorithm to improve. The research results also do a good bedding for the real-time clinical application of medical image segmentation algorithm.
	TO cite this article:Liu Changzheng,Guo Junfei,Xu Lei. The Research of Active Contour Optimization Model Based on Fast Marching Algorithm[OL].[16 January 2015] http://en.paper.edu.cn/en_releasepaper/content/4626915


	6. HMPC: A Multi-fields Fast Packet Classification Algorithm
	Tong Haiqi,Bao Xiuguo
	Computer Science and Technology 25 December 2014
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	Abstract:With the increasing popularity of Internet and new network applications, there has been a great concern on how to classify packets rapidly and accurately. In this paper we propose a Hash Multi-fields Packet Classification (HMPC) algorithm based on dimension decomposition. This algorithm maps the fields of the packet to the rule table through a single step, and then it combines the multi-fields mapping results via hash method. The HMPC algorithm can drastically improve space and time performance by adjusting the hash table structure design. The experimental results show that the space consumption of HMPC algorithm is 53% and 12% lower than Recursive Flow Classification (RFC) and Hierarchical Space Mapping (HSM) algorithms respectively, while maintaining a similar time performance with HSM.
	TO cite this article:Tong Haiqi,Bao Xiuguo. HMPC: A Multi-fields Fast Packet Classification Algorithm[OL].[25 December 2014] http://en.paper.edu.cn/en_releasepaper/content/4625278


	7. License Plate Recognition System Using a Coarse-to-fine Strategy
	Li Ang,Liu Liang
	Computer Science and Technology 23 December 2013
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	Abstract:This paper deals with problematic from field of image processing, artificial intelligence and machine vision in construction of a license plate recognition system. This issue includes mathematical principles and algorithms. The significant of this system is its robustness for Chinese license plate detection and recognition. Authors represent a coarse-to-fine strategy: license plate region's rough detection and accurate localization of the region of interest (ROI). For the Optical Character Recognition (OCR) task, a Probabilistic Neural Network (PNN) is trained to identify Chinese and alphanumberic characters. It turns out a high accuracy is achieved in experiments and the system has a good application prospect.
	TO cite this article:Li Ang,Liu Liang. License Plate Recognition System Using a Coarse-to-fine Strategy[OL].[23 December 2013] http://en.paper.edu.cn/en_releasepaper/content/4577610


	8. Texture Feature Clustering and Segmentation Algorithm based on Pixel
	Zhu Hong,Zhang Guoying
	Computer Science and Technology 10 August 2010
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	Abstract:As the coverage area of the sub-block is too large, the texture feature clustering based on sub-block often produces the mosaic phenomenon of inaccurate boundary. In this paper, the texture clustering algorithm based on pixel extracts the texture feature vector of its central pixel point from sub-block. The image texture feature is standardized, then the normalized feature vector is clustered and the clustering result is used to realize the segmentation of complex image. Compared with the traditional segmentation methods such as gradient method, threshold method and so on, the segmentation boundary is accurate, and the phenomenon of under-segmentation and over-segmentation also reduce significantly.
	TO cite this article:Zhu Hong,Zhang Guoying. Texture Feature Clustering and Segmentation Algorithm based on Pixel[OL].[10 August 2010] http://en.paper.edu.cn/en_releasepaper/content/4381224


	9. Mesh Topology in Scanned Garment Reconstruction
	Yueqi Zhong,Hongyan Liu
	Computer Science and Technology 26 February 2010
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	Abstract:3D garment with high fidelity can be obtained via range data scanning. The original output of body scanner is an unorganized points cloud. In this paper, the geometrical surface of 3D garment is reconstructed through a series of treatments. The primary target of this work is to investigate the dynamic behavior of the corresponding physical model transferred from different mesh topologies. A mass-spring model is constructed for both regular meshes and irregular meshes. The performance under various integration methods is evaluated. Experimental results reveal the procedure of regularization is suitable for the integrators that are sensitive to the physically-based simulation of scanned garments.
	TO cite this article:Yueqi Zhong,Hongyan Liu. Mesh Topology in Scanned Garment Reconstruction[OL].[26 February 2010] http://en.paper.edu.cn/en_releasepaper/content/40256


	10. ARM-Based Embedded Linux System For Wireless Video Monitor Applications
	zhou zhe
	Computer Science and Technology 11 September 2008
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	Abstract:Based on the combination of advanced RISC microprocessor (ARM) and embedded-Linux, this paper introduces a design for building wireless video monitor system. Compared with the wired mode, the wireless video monitor system extends the communication range and can be used in some adverse environment. This paper mainly describes the structure of our system. The result indicates the feasibility of our scheme.
	TO cite this article:zhou zhe. ARM-Based Embedded Linux System For Wireless Video Monitor Applications[OL].[11 September 2008] http://en.paper.edu.cn/en_releasepaper/content/23959

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