A knowledge-based approach for retrieving images by content

A knowledge based approach is introduced for retrieving images by content. It supports the answering of conceptual image queries involving similar-to predicates, spatial semantic operators, and references to conceptual terms. Interested objects in the images are represented by contours segmented from images. Image content such as shapes and spatial relationships are derived from object contours according to domain specific image knowledge. A three layered model is proposed for integrating image representations, extracted image features, and image semantics. With such a model, images can be retrieved based on the features and content specified in the queries. The knowledge based query processing is based on a query relaxation technique. The image features are classified by an automatic clustering algorithm and represented by Type Abstraction Hierarchies (TAHs) for knowledge based query processing. Since the features selected for TAH generation are based on context and user profile, and the TAHs can be generated automatically by a clustering algorithm from the feature database, our proposed image retrieval approach is scalable and context sensitive. The performance of the proposed knowledge based query processing is also discussed     

火焰动画快速模拟的新方法

针对火焰动画难以快速建模和绘制的问题,提出了完全利用GPU过程化生成火焰动画的高效算法。先用建模工具在预处理阶段构建一个由平面正方形组成的三维模型,在绘制阶段通过GPU编程对这些方形进行Billboard方式的变换,并用一些简单公式对他们的运动方式、大小和颜色来用过程化方式进行控制,最后通过alpha混合得到最终结果。算法完全在GPU里实现,能满足实时的绘制要求。     

结构正则化多视图非负矩阵分解

现存非负矩阵分解（non-negative matrix factorization,NMF）研究多考虑单一视图分解数据,忽略了数据信息的全面性。此外,NMF限制其获取数据的内在几何结构。针对以上问题,提出一个结构正则化多视图非负矩阵分解算法（structure regularized multi-view nonnegative matrix factorization,SRMNMF）。首先,通过主成分分析来对数据进行全局结构的判别式学习;其次,利用流形学习来捕获数据的局部结构;然后,通过利用多视图数据的多样性和差异性来学习表征。模型提升了算法聚类的整体性能,更加有效地挖掘数据的结构信息。此外,采用高效的交替迭代算法优化目标函数得到最优的因子矩阵。在六个数据集上与现存的代表性方法比较,所提出的SRMNMF的准确率、NMI和Purity分别最大提高4.4%、6.1%和4.05%。     

北京城区河流沉水植物分布特征及环境因子关系研究

通过北京城区11条河流30个点位沉水植物及水环境因子调查,对沉水物物种分布、生态位特征及与水环境因子相互关系进行了研究,结果表明:北京城区河流均有沉水植物分布,春季优势种为菹草、穗花狐尾藻和篦齿眼子菜,夏季为金鱼藻、狐尾藻、篦齿眼子菜、黑藻、苦草及菹草.水深为影响城区河流沉水植物种类数量的重要因子,菹草为春季沉水植物管理关键物种.研究城区河流沉水植物分布特征及与水环境因子的关系,对北京市河流水生态环境的管理和持续改善具有重要的参考和指导意义.     

Unsupervised Scale-Consistent Depth Learning from Video

International Journal of Computer Vision - We propose a monocular depth estimation method SC-Depth, which requires only unlabelled videos for training and enables the scale-consistent...     

A deep multi-source adaptation transfer network for cross-subject electroencephalogram emotion recognition

Neural Computing and Applications - In real-world application of affective brain–computer interface (aBCI), individual differences across subjects and non-stationary characteristics of...     

基于参数空间法的飞行器再入控制研究

针对空天飞行器再入段环境变化剧烈、气动参数变化范围大的特点,采用参数空间方法来设计其控制系统;首先建立飞行器控制系统的数学模型,鉴于飞行器再入过程中对攻角有着严格的要求,设计了以攻角反馈为被控信号的三回路自动驾驶仪结构,然后根据参数空间方法求出对应的控制器参数,最后基于Matlab/Simulink的非线性仿真表明,所设计的控制系统在大气密度偏差±30%、气动力/力矩系数各偏差±20%的组合偏差情况下仍具有较好的鲁棒稳定性和跟踪性能。     

光电火控系统指向精度CCD非接触测量方法研究

为满足某光电火控系统中二维转台指向精度的高精度测量需求,提出了一种利用CCD图像的非接触测量方法;以静态指向精度为测量对象,构建了CCD图像测量系统,系统分辨力为0.44mrad,采用视频序列的数字图像自动拼接方法得到单幅宽视场全景图,通过图像快速匹配方法得到转台的方位像素坐标值,对转台的指向精度进行了测量;测量实验结果表明:转台的指向精度为0.5mrad,满足指向精度2mrad的设计要求。     

Delay‐dependent stability for Markovian genetic regulatory networks with time‐varying delays

This paper is concerned with the problem of stochastic stability analysis for a class of genetic regulatory networks with Markovian jump parameters and time‐varying delays. A delay‐dependent stability criterion is derived by using a novel mode‐dependent Lyapunov functional. The derived stability criterion is expressed in terms of linear matrix inequalities and is less conservative than the existing ones in the literature. A numerical example is provided to demonstrate the effectiveness of the proposed stability criterion. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society