检索结果-南通市图书馆

Cross-media Hot Topic Auto-tracking Model Based on Semantics and Temporal Context

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2015年第3期24卷 529-534页

作者： liang meiyu DU Junping ZHOU Yipeng Beijing Key Lab of Intelligent Telecommunication Software and Multimedia School of Computer ScienceBeijing University of Posts and Telecommunications School of Computer and Information Engineering Beijing Technology and Business University

As the Internet multimedia information grows explosively, seeking an automatic technology to realize the effective organization and management of crossmedia emergency information is significantly necessary. A novel cross-media hot topic auto-tracking model based on semantics and temporal context is proposed in this paper. According to the semantic correlations of cross-media information, we learn the image visual semantics by the text semantics based on the Latent Dirichlet Allocation probability model, and establish the unified cross-media information description on the same semantic level. Also a semantics-based two-step feature dimension-reduction scheme is proposed to establish the efficient semantic feature space. The self-adaptive learning of topic model is realized to track the dynamic changes in the topic. Experimental results demonstrate that the proposed method outperforms the existing methods, which further improves the effect of hot topic auto-tracking.

关键词： Cross-media data mining Topic autotracking Semantic model Latent dirichlet allocation(LDA) Temporal context

Self-adaptive spatial image denoising model based on scale correlation and SURE-LET in the nonsubsampled contourlet transform domain

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2014年第9期57卷 72-86页

作者： liang meiyu DU JunPing LIU HongGang Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia School of Computer ScienceBeijing University of Posts and Telecommunications

A novel self-adaptive image denoising model based on scale correlation and Stein’s unbiased risk estimate-linear expansion of thresholds(SURE-LET)in the nonsubsampled contourlet transform domain is proposed in this *** we implement the multidimensional and translation invariant decomposition for spatial images by the nonsubsampled contourlet transform,and establish the image cross-scale description *** combining the scale correlation,we make improvements for the existing SURE-LET denoising idea and establish the self-adaptive denoising *** scale correlation calculation is needed for the coefficients at different scales and sub-bands to determine whether the coefficients are retained or processed with the adaptive SURE-LET threshold *** meanwhile a new local context self-adaptive threshold strategy is proposed in the process of scale correlation *** results both on spatial images and standard images demonstrate that the proposed algorithm performs significantly better in terms of both the visual subjective evaluation and the quantitative objective *** method can achieve better noise suppression,and effectively retain image edge details.

关键词： spatial images image denoising nonsubsampled contourlet transform SURE-LET scale correlation

Crowd Density Field Estimation Based on Crowd Dynamics Theory and Social Force Model

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2019年第3期28卷 521-528页

作者： WEI Xinlei DU Junping liang meiyu XUE Zhe Beijing Key Lab of Intelligent Telecommunication Software and Multimedia School of Computer ScienceBeijing University of Posts and Telecommunications

The local crowd density and the crowd distribution estimation tasks are useful but *** are two main problems which limit the performance of existing algorithms. The first one is that there are not enough labeled training samples to build the highperformance estimation model. Another one is that existing methods lack the supports of physical theories of the crowd. To remedy them, a novel crowd density field model is proposed, which is deduced by jointing crowd dynamics theory and social force model. A crowd counting method based on the proposed crowd density field model is introduced to measure the proposed crowd density field model. Extensive experiments confirm the effectiveness of the proposed plan.

关键词： Social force model Crowd dynamics Crowd density field Computer vision

Hierarchical-Based Object Detection with Improved Locality Sparse Coding

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2016年第2期25卷 290-295页

作者： ZHU Suguo DU Junping REN Nan liang meiyu Beijing Key Laboratory of Intelligent Telecommunication software and Multimedia School of Computer ScienceBeijing University of Posts and Telecommunications

This paper proposes to extend the hierarchical method to be adapted to sequential frames, aiming at detecting the moving object in dynamic scenes. A novel two-layer model is proposed, in which dictionaries are learned through three different stages and the locality constrained sparse representation is improved. This leads more significant improvement for performance of both static image classification and moving object detection. The experimental results demonstrate that the proposed algorithm is efficient and robust compared with the state-of-the-art classification methods, and also able to detect moving object in the sequential frames accurately.

关键词： Hierarchical detection Sparse coding Classification Object detection

《虚拟仪器技术》的项目化教学改革与实践探索

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

办公自动化 2024年第5期29卷 51-53,37页

作者：李胜梁美玉潘玥安徽信息工程学院芜湖241000

针对传统的《虚拟仪器技术》教学过程中理论与实践脱节,缺乏工程意识等问题,提出“一根本、二基础、三融合、一发挥”的项目化教学模式,分别从课程教学目标、思政建设目标、项目化建设方向和项目化建设重点4个维度介绍项目化教学建设,... 详细信息

针对传统的《虚拟仪器技术》教学过程中理论与实践脱节,缺乏工程意识等问题,提出“一根本、二基础、三融合、一发挥”的项目化教学模式,分别从课程教学目标、思政建设目标、项目化建设方向和项目化建设重点4个维度介绍项目化教学建设,依托项目化教学过程实施,实现“知识传授”与“价值引领”,加快专业课项目化建设步伐。

关键词：虚拟仪器技术工程意识项目化教学价值引领

Video super-resolution reconstruction based on deep convolutional neural network and spatio-temporal similarity

在线全文

学校读者我要写书评

暂无评论

The Journal of China Universities of Posts and Telecommunications 2016年第5期23卷 68-81页

作者： Li Linghui Du Junping liang meiyu Ren Nan Fan Dan Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia Beijing University of Posts and Telecommunications School of Computer Science Beijing University of Posts and Telecommunications

Existing learning-based super-resolution （SR） reconstruction algorithms are mainly designed for single image, which ignore the spatio-temporal relationship between video frames. Aiming at applying the advantages of learning-based algorithms to video SR field, a novel video SR reconstruction algorithm based on deep convolutional neural network （CNN） and spatio-temporal similarity （STCNN-SR） was proposed in this paper. It is a deep learning method for video SR reconstruction, which considers not onlv the mapping relationship among associated low-resolution （LR） and high-resolution （HR） image blocks, but also the spatio-temporal non-local complementary and redundant information between adjacent low-resolution video frames. The reconstruction speed can be improved obviously with the pre-trained end-to-end reconstructed coefficients. Moreover, the performance of video SR will be further improved by the optimization process with spatio-temporal similarity. Experimental results demonstrated that the proposed algorithm achieves a competitive SR quality on both subjective and objective evaluations, when compared to other state-of-the-art algorithms.

关键词： video SR reconstruction deep convolutional neural network spatio-temporal siruilarity Zernike moment feature

Astrocyte dysfunction in Parkinson's Check for updates disease:from the perspectives of transmittedα-synuclein and genetic modulation

在线全文

学校读者我要写书评

暂无评论

Translational Neurodegeneration 2021年第4期10卷 519-535页

作者： Changjing Wang Tongtong Yang meiyu liang Junxia Xie Ning Song Department of Physiology Shandong Provincial Key Laboratory of Pathogenesis and Prevention of Neurological DisordersSchool of Basic MedicineQingdao UniversityQingdao 266071China Institute of Brain Science and Disease Qingdao UniversityQingdao 266071China

Parkinson's disease(PD)is a common neurodegenerative disorder that primarily affects the *** the etiology of PD is likely multifactorial with the involvement of genetic,environmental,aging and other factors,α-synuclein(α-syn)pathology is a pivotal mechanism underlying the development of *** recent years,astrocytes have attracted considerable attention in the *** astrocytes perform a variety of physiological functions in the brain,they are pivotal mediators ofα-syn toxicity since they internalizeα-syn released from damaged neurons,and this triggers an inflammatory response,protein degradation dysfunction,mitochondrial dysfunction and endoplasmic reticulum *** are indispensable coordinators in the background of several genetic mutations,including PARK7,GBA1,LRRK2,ATP13A2,PINK1,PRKN and *** the most abundant glial cells in the brain,functional astrocytes can be replenished and even converted to functional *** this review,we discuss astrocyte dysfunction in PD with an emphasis onα-syn toxicity and genetic modulation and conclude that astrocyte replenishment is a valuable therapeutic approach in PD.

关键词： Parkinson's disease Astrocytes Genetic mutation α-synuclein Therapeutics

Spatio-Temporal Adaptive Super-Resolution Reconstruction Model Based on Zemike Moment for Spatial Video Sequences

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

China Communications 2012年第12期9卷 93-107页

作者： liang meiyu Du Junping JangMyung Lee Liu Honggang Zhang Yun Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia School of Computer Science Beijing University of Posts and Telecommunications Beijing 100876 P. R. China Department of Electronics Engineering Pusan Nation University Busan Korea

Video Super-Resolution （SR） reconstruction produces video sequences with High Resolution （HR） via the fusion of several Low-Resolution （LR） video frames. Traditional methods rely on the accurate estimation of subpixel motion, which constrains their applicability to video sequences with relatively simple motions such as global translation. We propose an efficient iterative spatio-temporal adaptive SR reconstruction model based on Zemike Moment （ZM）, which is effective for spatial video sequences with arbitrary motion. The model uses region correlation judgment and self-adaptive threshold strategies to improve the effect and time efficiency of the ZM-based SR method. This leads to better mining of non-local self-similarity and local structural regularity, and is robust to noise and rotation. An efficient iterative curvature-based interpolation scheme is introduced to obtain the initial HR estimation of each LR video frame. Experimental results both on spatial and standard video sequences demonstrate that the proposed method outperforms existing methods in terms of both subjective visual and objective quantitative evaluations, and greatly improves the time efficiency.

关键词： video super-resolution fuzzy registration scheme Zemike moment non-local self-similarity self-adaptive threshold

基于RNN和主题模型的社交网络突发话题发现

在线全文

学校读者我要写书评

暂无评论

通信学报 2018年第4期39卷 189-198页

作者：石磊杜军平梁美玉北京邮电大学智能通信软件与多媒体北京市重点实验室北京100876

社交网络数据是稀疏和嘈杂的,并伴有大量的无意义话题。传统突发话题发现方法无法解决社交网络短文本稀疏性问题,并需要复杂的后处理过程。为了解决上述问题,提出一种基于循环神经网络(RNN,recurrent neural network)和主题模型的突发... 详细信息

社交网络数据是稀疏和嘈杂的,并伴有大量的无意义话题。传统突发话题发现方法无法解决社交网络短文本稀疏性问题,并需要复杂的后处理过程。为了解决上述问题,提出一种基于循环神经网络(RNN,recurrent neural network)和主题模型的突发话题发现(RTM-SBTD)方法。首先,综合RNN和逆序文档频率(IDF,inverse document frequency)构建权重先验来学习词的关系,同时通过构建词对解决短文本稀疏性问题。其次,模型中引入针板先验(spike and slab)来解耦突发话题分布的稀疏和平滑。最后,引入词的突发性来区分建模普通话题和突发话题,实现突发话题自动发现。实验结果表明与现有的主流突发话题发现方法相比,所提RTM-SBTD方法在多种评价指标上优于对比算法。

关键词：社交网络突发话题发现主题模型循环神经网络