检索结果-内蒙古大学图书馆

ENTF: An entropy-based MT evaluation metric 1

13th China Workshop on Machine Translation, CWMT 2017

作者： Yu, Hui Xu, Weizhi Lin, Shouxun Liu, Qun School of Management Science and Engineering Shandong Normal University Jinan China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China ADAPT Centre School of Computing Dublin City University Dublin Ireland

ISBN: (数字)9789811071348

ISBN: (纸本)9789811071331

The widely-used automatic evaluation metrics cannot adequately reflect the fluency of the translations. The n-gram-based metrics, like BLEU, limit the maximum length of matched fragments to n and cannot catch the matched fragments longer than n, so they can only reflect the fluency indirectly. METEOR, which is not limited by n-gram, uses the number of matched chunks but it does not consider the length of each chunk. In this paper, we propose an entropy-based metric (ENTF), which can sufficiently reflect the fluency of translations through the distribution of matched words. To evaluate the accuracy, we also introduce the unigram F-score into the new metric. Experiment shows that ENTF obtains state-of-the-art performance on system level, and is comparable with METEOR on sentence level on into English direction on WMT 2012, WMT 2013 and WMT 2014. © Springer Nature Singapore Pte Ltd. 2017.

关键词： Entropy

来源：评论

学校读者我要写书评

暂无评论

Emergency Event Matching using Hierarchical Blocking Method

引用

Journal of Physics: Conference Series 2019年第5期1187卷

作者： Chang Wen Yu Liu College of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Intelligent Information Processing and Real-time Industrial System in Hubei Province Wuhan 430065 China Institute of Big Data Science and Engineering Wuhan University of Science and Technology Wuhan 430065 China Key Laboratory of Rich-media Knowledge Organization and Service of Digital Publishing Content National Press and Publication Administration Beijing 100038 China

With the extensive application of the knowledge base (KB), how to complete it is a hot topic on Semantic Web. However, many problems go with the big data, and the event matching is one of these problems, which is finding out the entities referring to the same things in the real world and also the key point in the extending process. To enrich the emergency knowledge base (E-SKB) we constructed before, we need to filter out the news from several web pages and find the same news to avoid data redundancy. In this paper, we proposed a hierarchy blocking method to reduce the times of comparisons and narrow down the scope by extracting the news properties as the blocking keys. The method transforms the event matching problem into a clustering problem. Experimental results show that the proposed method is superior to the existing text clustering algorithm with high precision and less comparison times.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Chinese and Thai bilingual topic detection online 13

Chinese and Thai bilingual topic detection online

引用

13th Global Congress on Manufacturing and Management, GCMM 2016

作者： Rang, Ziqiang Zhou, Lanjiang Zhang, Jinpeng Xian, Yantuan Yu, Zhengtao School of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Key Laboratory of Intelligent Information Processing Kunming University of Science and Technology Kunming Yunnan650500 China Information Management Center Yunnan University Of Finance and Economics Kunming Yunnan650500 China

Bilingual topic detection is a vital application of natural language processing in the Internet plus Era and trend of economic globalization. At present, the method of bilingual topic detection can't solve the problem of bilingual topic inconsistent distribution. Aiming at the shortcoming, this paper introduces a based on maximal clique method to find bilingual topic detection of Chinese and Thai feature words. First of all, extract the information of news with keywords of each Chinese and Thai documents through the TextRank algorithm. Next, disambiguate by means of the similarity combined with Chinese and Thai dictionary. Then, use credible association rules to cluster Chinese and Thai feature words, which generates maximal clique of bilingual topic. Finally, cluster similar maximal clique of topic to obtain the collection of final topic. According to the needs of users, the method can recommend a bilingual topic of different sizes. The test of Chinese and Thai news texts in January 2016 made good achievement. From the perspective of cross-language word clustering, the algorithm effectively solves the problem of inconsistency of bilingual topic distribution reasonably, and has the advantages of no need to estimate the number of topics and low time complexity, so it is suitable for the application of online discovery in bilingual topic. © The Authors, published by EDP Sciences.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Research on fast self-learning improvement of ADRC control algorithm for film thickness control system

引用

Journal of Physics: Conference Series 2019年第3期1187卷

作者： Liao Xue-chao Zhou You Chen Zhen-huan School of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430081 P. R. China Tel.: +86-*** Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan 430081 P. R. China Tel.: +86-***

In the biaxially stretched film (BOPP) thickness control system, the traditional PID and Active-Disturbance Rejection Controller (ADRC) can't achieve the ideal control effect. The Smith prediction method is used in the essay to establish a discretization model for the BOPP thickness control system. Combining with BP self-learning algorithm, a fast self-learning improved ADRC control algorithm (FSADRC) is proposed. By means of the additional momentum term and the adaptive learning rate method, the nonlinear combination of the ADRC system is adjusted in real time, the optimal control parameters are found, and the parameters are self-tuned. As a consequence, the improved algorithm is applied to the biaxial tensile film thickness control model. The simulation results show that the method has the advantages of high response speed and strong self-adaptive ability, which can effectively improve the control performance of the BOPP thickness control system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Effects of RapidEye Imagery's Red-edge Band and Vegetation Indices on Land Cover Classification in an Arid Region

引用

Chinese Geographical Science 2017年第5期27卷 827-835页

作者： LI Xianju CHEN Gang LIU Jingyi CHEN Weitao CHENG Xinwen LIAO Yiwei College of Computer Science and Hubei Key Laboratory of Intelligent Geo-Information Processing China University of GeosciencesWuhan 430074China College of Marine Science and Technology China University of GeosciencesWuhan 430074China Laboratory of Geographic Information and Spatial Analysis Department of Geography and PlanningQueen's UniversityKingston ON K7L3N6Canada Faculty of Information Engineering China University of GeosciencesWuhan 430074China School of Electrical and Electronic Engineering Huazhong University of Science and TechnologyWuhan 430074China

Land cover classification(LCC) in arid regions is of great significance to the assessment, prediction, and management of land desertification. Some studies have shown that the red-edge band of RapidE ye images was effective for vegetation identification and could improve LCC accuracy. However, there has been no investigation of the effects of RapidE ye images' red-edge band and vegetation indices on LCC in arid regions where there are spectrally similar land covers mixed with very high or low vegetation coverage information and bare land. This study focused on a typical inland arid desert region located in Dunhuang Basin of northwestern China. First, five feature sets including or excluding the red-edge band and vegetation indices were constructed. Then, a land cover classification system involving plant communities was developed. Finally, random forest algorithm-based models with different feature sets were utilized for LCC. The conclusions drawn were as follows: 1) the red-edge band showed slight contribution to LCC accuracy; 2) vegetation indices had a significant positive effect on LCC; 3) simultaneous addition of the red-edge band and vegetation indices achieved a significant overall accuracy improvement(3.46% from 86.67%). In general, vegetation indices had larger effect than the red-edge band, and simultaneous addition of them significantly increased the accuracy of LCC in arid regions.

关键词： arid region land cover classification RapidEye red-edge band vegetation indices random forest Dunhuang Basin

来源：评论

学校读者我要写书评

暂无评论

Motion deblurring based on convolutional neural network 12th

Motion deblurring based on convolutional neural network

引用

12th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2017

作者： Tan, Yunfei Zhang, Di Xu, Fei Zhang, Danyang Department of Physical Education Huazhong University of Science and Technology WuhanHubei430074 China Key Laboratory of Image Information Processing Intelligent Control of Education Ministry of China School of Automation Huazhong University of Science and Technology WuhanHubei430074 China JamaicaNY11451 United States

ISBN: (纸本)9789811071782

Object motion blur results when the object in the scene moves during the recording of a single exposure, either due to too rapid movement or long exposure, leaving streaks of the moving object in the image and thus degrading its quality. In this paper, we present a method to solve the object motion blur problem in images with clear static background. Specifically, we propose an object motion deblurring algorithm that uses a convolutional neural network with six convolutional layers to deblur the image. Taking advantages of the strong ability of feature learning in convolutional neural networks, our method can remove the blurring effect of fast-moving object while keeping the clear background untouched. It is well known that neural networks are best driven by large data sets and more data means more benefits for training convolutional neural networks;therefore, we generated training set of 144,000 images and test set of 32,400 images. Through carefully designed training process, our model learned the ability of deblurring the blurred object while keeping the clear background. The experiment results show that our approach can generate superior results to a representative image deblurring algorithm that treats the same blurred object and clear background. © Springer Nature Singapore Pte Ltd 2017.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Accelerating electron tomography reconstruction algorithm ICON with GPU

引用

Biophysics Reports 2017年第Z1期3卷 36-42页

作者： Yu Chen Zihao Wang Jingrong Zhang Lun Li Xiaohua Wan Fei Sun Fa Zhang Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences National Key Laboratory of Biomacromolecules CAS Center for Excellence in Biomacromolecules Institute of Biophysics Chinese Academy of Sciences University of Chinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences Center for Biological Imaging Institute of Biophysics Chinese Academy of Sciences

Electron tomography(ET) plays an important role in studying in situ cell ultrastructure in threedimensional space. Due to limited tilt angles, ET reconstruction always suffers from the "missing wedge" problem. With a validation procedure, iterative compressed-sensing optimized NUFFT reconstruction(ICON) demonstrates its power in the restoration of validated missing information for low SNR biological ET dataset. However, the huge computational demand has become a major problem for the application of ICON. In this work, we analyzed the framework of ICON and classified the operations of major steps of ICON reconstruction into three types. Accordingly, we designed parallel strategies and implemented them on graphics processing units(GPU) to generate a parallel program ICON-GPU. With high accuracy, ICON-GPU has a great acceleration compared to its CPU version, up to 83.7×, greatly relieving ICON’s dependence on computing resource.

关键词： Acceleration Electron tomography GPU ICON Missing wedge restoration

来源：评论

学校读者我要写书评

暂无评论

Collaborative model in brain-computer integration 2nd

Collaborative model in brain-computer integration

引用

2nd IFIP TC 12 International Conference on Intelligence Science, ICIS 2017

作者： Shi, Zhongzhi Ma, Gang Li, Jianqing Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Shandong University No. 27 Shan Da Nan Road JinanShandong China

ISBN: (纸本)9783319681207

Brain-computer integration is a new intelligent system based on brain-computer interface technology, which is integrated with biological intelligence and artificial intelligence. In order to make this integration effective and co-adaptive biological brain and machine should work collaboratively. ABGP-CNN based environment awareness and motivation driven collaboration will be presented in the paper. Motivation is the cause of action and plays important roles in collaboration. The motivation leaning method and algorithm will be explored in terms of event curiosity, which is useful for sharing common interest situations. © IFIP International Federation for Information processing 2017.

关键词： Motivation

来源：评论

学校读者我要写书评

暂无评论

An Anti-Eavesdrop Transmission Scheduling Scheme Based on Maximizing Secrecy Outage Probability in Ad Hoc Networks

引用

China Communications 2016年第1期13卷 176-184页

作者： WANG Yajun LIAO Tongqing WANG Chuanan School of Mathematical and Information Engineering Anhui Science and Technology University Ministry of Educational Key Laboratory of Intelligent Computing and Signal Processing Anhui University

In this paper,we consider a wireless ad hoc network consisting of multiple source nodes transmitting to their respective destinations,where an eavesdropper attempts to intercept their *** propose an optimal transmission scheduling scheme to defend against the eavesdropper,where a source node having the highest secrecy rate is scheduled to access the wireless medium for transmitting to its destination in an opportunistic *** be specific,the secrecy rate between a pair of the source and destination in the presence of an eavesdropper varies temporally due to the wireless fading *** proposed optimal transmission scheduling scheme opportunistically selects a source node with the highest secrecy rate to transmit its data for the sake of maximizing the security of the ad hoc network against eavesdropping *** comparison purposes,we also consider the conventional round-robin scheduling as a benchmark,where multiple source nodes take turns in accessing their shared wireless medium for transmitting to their respective *** derive closed-form secrecy outage probability expressions of both the round-robin scheduling and the proposed optimal scheduling schemes over Rayleigh fading *** results show that the proposed transmission scheduling scheme outperforms the conventional round-robin method in terms of its secrecy outage ***,upon increasing the number of source-destination pairs,the secrecy outage probability of the round-robin scheme keeps unchanged,whereas the secrecy outage performance of the proposed transmission scheduling significantly improves,showing the security benefits of exploiting transmission scheduling for protecting wireless ad hoc networks against eavesdropping.

关键词： transmission scheduling eavesdropping secrecy outage probability secrecy rate rayleigh fading

来源：评论

学校读者我要写书评

暂无评论

Data association based multi-target tracking using a joint formulation

Lecture Notes in Computer Science (including subseries Lectu...

引用

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2017年 10114 LNCS卷 240-255页

作者： Xiang, Jun Hou, Jianhua Gao, Changxin Sang, Nong National Key Laboratory of Science and Technology on Multispectral Information Processing School of Automation Huazhong University of Science and Technology Wuhan China Hubei Key Laboratory of Intelligent Wireless Communications South-Central University for Nationalities Wuhan China

ISBN: (纸本)9783319541891

We revisit the classical conditional random filed based tracking-by-detection framework for multi-target tracking, in which function factors associating pairs of short tracklets in a long term are modeled to produce final tracks. Unlike most previous approaches which only focus on modeling feature difference for distinguishing pairs of targets, we propose to directly model the joint formulation of pairs of tracklets for association in the CRF framework. To this end, we use a Hough Forest (HF) based learning framework to effectively learn a discriminative codebook of features among tracklets by utilizing appearance and motion cues stored in the leaf nodes. Given the learned codebook, the joint formulation of tracklet pairs can be directly modeled in a nonparametric manner by defining a sharing and excluding matrix. Then all of the statistics required in CRF inference can be directly estimated. Extensive experiments have been conducted on several public datasets, and the performance is comparable to the state of the art. © Springer International Publishing AG 2017.

关键词： Clutter (information theory)

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：