Construction and verification of retinal vessel segmentation algorithm for color fundus image under BP neural network model

To improve the accuracy of retinal vessel segmentation, a retinal vessel segmentation algorithm for color fundus images based on back-propagation (BP) neural network is proposed according to the characteristics of retinal blood vessels. Four kinds of green channel image enhancement results of adaptive histogram equalization, morphological processing, Gaussian matched filtering, and Hessian matrix filtering are used to form feature vectors. The BP neural network is input to segment blood vessels. Experiments on the color fundus image libraries DRIVE and STARE show that this algorithm can obtain complete retinal blood vessel segmentation as well as connected vessel stems and terminals. When segmenting most small blood vessels, the average accuracy on the DRIVE library reaches 0.9477, and the average accuracy on the STARE library reaches 0.9498, which has a good segmentation effect. Through verification, the algorithm is feasible and effective for blood vessel segmentation of color fundus images and can detect more capillaries.

     

农村抽样调查中的抽样框问题

准确、完备的抽样框是抽样调查的前提条件,对农村抽样框的选择应考虑到中国农村具体情况,不能照搬城市调查的方法。分析了抽样框老化、遗漏目标等四种抽样框误差类型,并结合中国农村实际,提出入乡随俗、多方合作、加强过程控制、户籍制度改革等建议。     

以企业为主体的技术创新体系的五维度分析

以企业为主体的技术创新体系是推进我国全面技术创新的重要动力, 然而众多因素影响着企业在技术创新体系中的主体性.基于理论分析和问卷调研, 通过调研样本的探索性分析和可靠性分析探索了影响企业在技术创新体系中主体性的因素, 提出了我国以企业为主体的技术创新体系的5个维度, 建立了以企业为主体的技术创新体系5维度的结构方程模型, 同时验证了若干重要假设.     

Exact and approximate flexible aggregate similarity search

Aggregate similarity search, also known as aggregate nearest-neighbor (Ann) query, finds many useful applications in spatial and multimedia databases. Given a group Q of M query objects, it retrieves from a database the objects most similar to Q, where the similarity is an aggregation (e.g., \({{\mathrm{sum}}}\), \(\max \)) of the distances between each retrieved object p and all the objects in Q. In this paper, we propose an added flexibility to the query definition, where the similarity is an aggregation over the distances between p and any subset of \(\phi M\) objects in Q for some support \(0< \phi \le 1\). We call this new definition flexible aggregate similarity search and accordingly refer to a query as a flexible aggregate nearest-neighbor ( Fann ) query. We present algorithms for answering Fann queries exactly and approximately. Our approximation algorithms are especially appealing, which are simple, highly efficient, and work well in both low and high dimensions. They also return near-optimal answers with guaranteed constant-factor approximations in any dimensions. Extensive experiments on large real and synthetic datasets from 2 to 74 dimensions have demonstrated their superior efficiency and high quality.     

结合船舶工程建设需求 探讨我国自主CAE软件产业建设

针对我国缺乏自主CAE软件的现况,结合船舶工程建设的创新发展需求,探讨建设自主CAE软件产业的可行性.阐述政府在政策和经济上扶持的重要性,指出生产性服务业、先进制造业与自主CAE软件产业联动对我国船舶工业自主创新发展的必要性.     

独立学院计算机专业课程设置研究

本文分析了独立学院计算机专业教育的现状,并提出了"注重基础,拓展模块,项目驱动,校企结合"的课程设置思路,以提高大学生的专业技能,促进就业。     

在Debian上用DRBD实现MySQL群集

本文旨在Debian系统上,创建一个基于DRBD磁盘镜像技术的MySQL群集及故障转移方法,同时使用了负载均衡技术来完善系统。     

网络攻击的防范策略

近年来计算机网络受到攻击及瘫痪的现象频频发生,给企业和社会造成极大的经济损失,在社会上影响极坏。因此,除了传统的预防方法之外,为改变这种被动受攻击的局面,本文对网络攻击的防范策略进行了探讨。     

Few-shot node classification via local adaptive discriminant structure learning

Node classification has a wide range of application scenarios such as citation analysis and social network analysis. In many real-world attributed networks, a large portion of classes only contain limited labeled nodes. Most of the existing node classification methods cannot be used for few-shot node classification. To train the model effectively and improve the robustness and reliability of the model with scarce labeled samples, in this paper, we propose a local adaptive discriminant structure learning (LADSL) method for few-shot node classification. LADSL aims to properly represent the nodes in the attributed graphs and learn a metric space with a strong discriminating power by reducing the intra-class variations and enlarging inter-class differences. Extensive experiments conducted on various attributed networks datasets demonstrate that LADSL is superior to the other methods on few-shot node classification task.