非参数岸岛背景红外舰船目标识别算法研究

由于战场环境复杂且瞬息万变,针对岸岛背景引入了一种快速 的检测/定位算法。该算法能够搜索出感兴趣的红外舰船目标,比如停靠在港口的舰船,而且无需 预先训练。这种方法仅仅使用一幅单一的目标物体样例图片来发现视场中相似的匹配舰 船,而无需对要搜索的物体进行预先学习。从查询图像中提取局部方向核 作为描述器,用于度量一个像素与其邻域间的相似度。然后从这个描述器中提取出显著 特征,并将其与目标图像中的类似特征进行比较。这些比较是使用一个余弦相似度度量矩阵 来实现的。实验结果表明,这个算法表现优异,成功地识别出了复杂背景条件下的舰船目标。     

基于实例的检索

基于实例的推理是人工智能中一项重要推理技术,而推理的核心是检索.介绍了产品设计的相似度计算方法,以及实例特征参数权系数值的确定方法,最后给出产品设计实例库三级检索算法.     

Software lens compensation applied to athermalization of infrared imaging systems

A different approach, aiming to achieve the constant blur status of point-spread function (PSF) at a certain defocused plane, is described. The correlation between the two PSF is used to control the PSF blur similarity, and simultaneously the Strehl ratio is also used to control the PSF blur minimization. By designing the PSF so that it is significantly insensitive to defocus or related defocus quantity, for example, due to temperature change, all the constantly blurred images can be accurately de-blurred by a simple inverse restoration filter for an adequate range of defocus. We refer to that as “software lens compensation” and apply a design method to solve the athermalization of middle wavelength infrared (MWIR) imaging systems. The resultant PSF is almost invariant in the temperature range from −10 to 50°C at the same focal plane. Consequently, the constant blur spot can be removed by a simple digital signal processing. Thus, clear and sharp de-blurred images at different temperatures are obtained.     

A two-stage shape retrieval (TSR) method with global and local features

A robust two-stage shape retrieval (TSR) method is proposed to address the 2D shape retrieval problem. Most state-of-the-art shape retrieval methods are based on local features matching and ranking. Their retrieval performance is not robust since they may retrieve globally dissimilar shapes in high ranks. To overcome this challenge, we decompose the decision process into two stages. In the first irrelevant cluster filtering (ICF) stage, we consider both global and local features and use them to predict the relevance of gallery shapes with respect to the query. Irrelevant shapes are removed from the candidate shape set. After that, a local-features-based matching and ranking (LMR) method follows in the second stage. We apply the proposed TSR system to MPEG-7, Kimia99 and Tari1000 three datasets and show that it outperforms all other existing methods. The robust retrieval performance of the TSR system is demonstrated.     

浅析图像领域PCT申请的补充检索

图像领域PCT申请通常存在丰富的已有信息,且技术方案复杂度较高.针对图像领域PCT申请补充检索的典型情况,给出了相应的补充检索策略,并通过实际案例验证了上述补充检索策略的有效性.审查员应灵活运用相应的补充检索策略,提高检索的有效性.     

国外互联网新业务信息安全管理对策

由于互联网新业务具有较强的不可预见性．因此对于互联网新业务发展中所带来的信息安全问题。互联网新业务种类不断翻新，从监管的视角出发，互联网新业务基本可以划分为三个大类：社区类、信息发布类和信息检索类。本文将分别介绍国外对社区类、信息发布类和信息检索类互联网新业务的管理对策。     

词频规范化改善信息检索查准率

研究了词频规范化，通过实例指出并分析了极大规范化词频、对数词频和平均词频这3种现有的词频规范化方法的不足，在理论上探究了影响词频规范化的因素。通过引入新参数的方法对词频规范化予以改进，以试错法给出了3种可能的词频规范化形式，并经数学推导，最终给出了改进的词频规范化方法，并通过实验验证了改进的词频规范化形式的有效性。     

Inflow conditions for spatial direct numerical simulation of turbulent boundary layers

The inflow conditions for spatial direct numerical simulation (SDNS) of turbulent boundary layers should reflect the characteristics of upstream turbulence, which is a puzzle. In this paper a new method is suggested, in which the flow field obtained by using temporal direct numerical simulation (TDNS) for fully developed turbulent flow (only flow field for a single moment is sufficient) can be used as the inflow of SDNS with a proper transformation. The calculation results confirm that this method is feasible and effective. It is also found that, under a proper time-space transformation, all statistics of the fully developed turbulence obtained by both temporal mode and spatial mode DNS are in excellent agreement with each other, not only qualitatively, but also quantitatively. The normal-wise distributions of mean flow profile, turbulent Mach number and the root mean square (RMS) of the fluctuations of various variables, as well as the Reynolds stresses of the fully developed turbulence obtained by using SDNS, bear similarity in nature. Supported by the National Natural Science Foundation of China (Grant No. 90205021), the China Postdoctoral Science Foundation (Grant No. 20060400707), and the Foundation for the Author of National Excellent Doctoral Dissertation of China (Grant No. 200328), and partially supported by Liu-Hui Center of Applied Mathematics, Nankai University and Tianjin University