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	1. Research on entity extraction of demand for industry-university-research projects based on BERT-BiLSTM-CRF
	ZHANG Zhiqing,TAO Zekui
	Computer Science and Technology 04 January 2024
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	Abstract:In order to realize the effective docking between schools and enterprises in industry-university-research cooperation projects and accurately obtain the technical needs of enterprises, based on the characteristics of concise and diversified texts of industry-university-research projects, a Chinese named entity extraction method based on BERT+BiLSTM+CRF model was proposed. Firstly, the BERT model is used to encode the input text, then the BiLSTM model is used to model the context to capture more comprehensive context information, and finally the label decoding is carried out through the CRF layer to obtain the optimal entity annotation results. Experimental results show that the proposed method is effective and feasible, and the extraction effect is better than that of the traditional method, which provides the possibility to solve the difficulties of technical demand information extraction, such as polysemy and language variants.
	TO cite this article:ZHANG Zhiqing,TAO Zekui. Research on entity extraction of demand for industry-university-research projects based on BERT-BiLSTM-CRF[OL].[ 4 January 2024] http://en.paper.edu.cn/en_releasepaper/content/4761868


	2. A novel key frame selection method for aerial image stitching by integrating navigation information and trusted key points
	Zheng Yongji,Wang Guoyou
	Computer Science and Technology 01 April 2021
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	Abstract:Fast and high-precision video based image stitching plays an important role in many machine vision applications, such as UAV mapping and reconnaissance. Due to the large number of frames and high redundancy of video sequence, image stitching is very time-consuming. Therefore, from the perspective of reducing the number of redundant frames, this paper proposes a novel video sequence key frame selection method based on rough camera external parameters and key point fusion, which selects the appropriate key frames by optimizing the overlap rate and the number of reliable key points between two adjacent key frames. The algorithm not only greatly reduces the number of key frames, but also ensures the reliable video mosaic. The experimental results on Bu S\' videos show that our method can reduce the number of key frames by 92%. In addition, compared with the key frame selection method based only on navigation information, this method also overcomes the problem of missing stitched images caused by insufficient key points in overlapping regions.
	TO cite this article:Zheng Yongji,Wang Guoyou. A novel key frame selection method for aerial image stitching by integrating navigation information and trusted key points[OL].[ 1 April 2021] http://en.paper.edu.cn/en_releasepaper/content/4754321

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	3. Head Pose Estimation Based on Dlib and Savitzky-Golay Smoothing Algorithm
	LU Xiaoning,LIU Wen
	Computer Science and Technology 18 January 2021
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	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


	4. An Improved Visual-Inertial Odometry Based on Self-Adaptive Attention-Anticipation Feature Selector
	Ruan Wenlong,Wang Jing
	Computer Science and Technology 22 November 2019
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	Abstract:Visual inertia odometers have achieved great success with the development of robot vision. However, it remains a challenging problem to achieve robust and efficient pose estimation on low-power platforms such as smartphones. This paper proposes a new visual inertial odometer scheme for low-power platforms, named visual inertial odometer based on adaptive attention-anticipation mechanism, which adds visual information to the VINS-based visual inertial odometer. The attention distribution module and the motion information forward anticipation module are controlled by the adaptive adjustment module to reduce the system operation load and improve the system tracking accuracy. We contribute in the following three aspects: 1) A attention mechanism for visual inertia history is proposed, which provides visual attention distribution for system radical motion in complex space environment, and extracts vision with high weight on system influence. Feature tracking; 2) A visual feature screening mechanism based on motion prediction is proposed to filter the visual features that will escape the camera perspective in advance; 3) use the adaptive adjustment module for front-end control and efficiently allocate restricted computing resources. Our approach achieves advanced estimation performance on the Euroc MAV datasets.
	TO cite this article:Ruan Wenlong,Wang Jing. An Improved Visual-Inertial Odometry Based on Self-Adaptive Attention-Anticipation Feature Selector[OL].[22 November 2019] http://en.paper.edu.cn/en_releasepaper/content/4750006


	5. Study on Circle Detection Algorithm based on Data Dispersion
	WEI Youying,SHUAI Liguo,CHEN Huiling
	Computer Science and Technology 26 January 2016
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	Abstract:Keywords: circle detection, center coordinates, dispersion To reduce time-consuming, a new algorithm for circle detection is proposed based on data dispersion. The center coordinates and radius can be detected with five steps in this algorithm precisely and quickly; firstly, to reduce the original circle to single-pixel width circle with image processing. Secondly, to calculate the center coordinates with three arbitrary points on the circle. There might be a deviation between the calculated center and real center. Thirdly, to determine a square area for the center coordinates computing with an experimental range and each pixel inside the square is a potential center. Fourthly, to compute the center with distance criterion and the center coordinate is determined when the variance reaches the minimum. Lastly, the radius is equal to the means of the distance vector with the minimum variance. Experiments are conducted and the results show that, comparing with the traditional Hough transform, the new algorit?????
	TO cite this article:WEI Youying,SHUAI Liguo,CHEN Huiling. Study on Circle Detection Algorithm based on Data Dispersion[OL].[26 January 2016] http://en.paper.edu.cn/en_releasepaper/content/4677465


	6. Zooming image by a combination of bi-cubic polynomial with edges as twice constraints
	LIU Ye-Penguin, ZHANG Cai-Ming
	Computer Science and Technology 03 December 2015
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	Abstract:The clarity and efficiency of the generated image is an important indicator which measures the quality of image zooming. Compared image which is obtained by existed zooming algorithm with the real images, it is more blurrier and consumes much time. On the basis of the existing scaling algorithm, this paper presents a zooming image by a combination of bi-cubic polynomial with edges as twice constraints algorithm. Algorithm is divided into two parts, in the first process, suppose the original scene surface corresponding to given data of the image can be represented by piecewise quadratic polynomial surface, and we can obtain the fitting surface by reversing of solving the image data. Then,by integrated to he fitting surface we can obtain a zooming image which is more blurrier in visual and fidelity. The initial image contains a lot of details of the information, but does not reflect visually. In the second process, it is the purpose that extracts the hide information and makes the image has better visual effect. By comparison, the new algorithm has better amplification effect and higher precision in visual, and spent less time.
	TO cite this article:LIU Ye-Penguin, ZHANG Cai-Ming. Zooming image by a combination of bi-cubic polynomial with edges as twice constraints[OL].[ 3 December 2015] http://en.paper.edu.cn/en_releasepaper/content/4666447


	7. Design and Implementation of Semantic Resource Management Platform Based on LDAP
	WU Keqiao,LIU Chuanchang
	Computer Science and Technology 05 December 2014
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	Abstract:With the development of information technology, more and more social resources haven been information. But managing resources platforms with resource semantic annotation is infrequent. LDAP (Lightweight directory access protocol) is applied widely for its simplicity and integrity. OWL (Ontology Web Language) is widely used in the definition of ontology following the continually maturation of semantic web. With, its lightweight property, REST is usually selected to develop business service. So based on LDAP and ontology modeling, this paper provides a approach to design and implement SRMP (Semantic Resource Management Platform), and opens the CRUD (create, 3retrieve, update, delete) operation of resources with restful style.
	TO cite this article:WU Keqiao,LIU Chuanchang. Design and Implementation of Semantic Resource Management Platform Based on LDAP[OL].[ 5 December 2014] http://en.paper.edu.cn/en_releasepaper/content/4620844


	8. An Opposition Effective GSA Based Memetic Algorithm for Permutation Flow Shop Scheduling
	ZHOU Junping,WANG Huixian,SU Weihua
	Computer Science and Technology 25 February 2014
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	Abstract:The permutation flow shop problem (PFSSP) is a well-known difficult combinatorial optimization problem. In this paper, we present a new hybrid optimization algorithm named OHGSA to solve the PFSSP. First, to make GSA suitable for PFSSP, a new LRV rule based on random key is introduced to convert the continuous position in GSA to the discrete job permutation. Second, The NEH heuristic was combined the random initialization to initialize the population with certain quality and diversity. Third, to improve the convergence rate of GSA, the opposition-based DE employs opposition-based learning for the initialization and for generation jumping to enhance the global optimal solution. Fourth, the fast local search is used for enhancing the individuals with a certain probability. Additional-ly, Comparison with other results in the literature shows that the OHGSA is an ef-ficient and effective approach for the PFSSP.
	TO cite this article:ZHOU Junping,WANG Huixian,SU Weihua. An Opposition Effective GSA Based Memetic Algorithm for Permutation Flow Shop Scheduling[OL].[25 February 2014] http://en.paper.edu.cn/en_releasepaper/content/4587358


	9. Real-time Road Detection with Image Texture Analysis-based Vanishing Point Estimation
	ZU Zhaozi,XUE Jianru,CUI Dixiao
	Computer Science and Technology 13 January 2013
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	Abstract:Visual perception is a key component of an autonomous vehicle system. Road detection is an essential function of a visual navigation system for an autonomous vehicle. In most cases detecting lane markings is one feasible and efficient approach to road detection. However, in some situation, for example, many rural roads have no lane markings. Furthermore, lacking of sharp, smooth edges and homogeneous surface brings difficulties to road detection. A texture analysis based vanishing point estimation method is used to detect road in this paper. The idea is that consistency in texture leads to the vanishing point in an image. The method uses the Sobel filter to compute the texture orientations. Then the vanishing point of the road is voted from the orientation of the texture. Finally, the vanishing point is used to constrain the searching of two road boundaries since they pass through the vanishing point.
	TO cite this article:ZU Zhaozi,XUE Jianru,CUI Dixiao. Real-time Road Detection with Image Texture Analysis-based Vanishing Point Estimation[OL].[13 January 2013] http://en.paper.edu.cn/en_releasepaper/content/4506414


	10. A Malware Detection Algorithm Based on Multi-view Fusion
	Guo Shanqing,Yu Qixia,Lin Fengbo,Wang Fengyu,Ban Tao
	Computer Science and Technology 05 January 2013
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	Abstract:One of the major problems concerning information assurance is malicious code. In order to detect them, many existing run-time intrusion or malware detection techniques utilize information available in Application Programming Interface (API) call sequences to discriminate between benign and malicious processes. Although some great progresses have been made, the new research results of ensemble learning make it possible to design better malware detection algorithm. This paper present a novel approach of detecting malwares using API call sequences. Basing on the fact that the API call sequences of a software show local property when doing network, file IO and other operations, we first divide the API call sequences of a malware into seven subsequences, and then use each subsequence to build a classification model. After these building models are used to classify software, their outputs are combined by using BKS and the final fusion results will be used to label whether a software is malicious or not. Experiments show that our algorithm can detect known malware effectively.
	TO cite this article:Guo Shanqing,Yu Qixia,Lin Fengbo, et al. A Malware Detection Algorithm Based on Multi-view Fusion[OL].[ 5 January 2013] http://en.paper.edu.cn/en_releasepaper/content/4504580

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