基于Protégé的领域本体构建研究

介绍了领域本体构建的基本流程,目的是为了更好地服务于语义web以及搜索引擎等。主要内容包括本体的概念、分类、功能及本体构建的方法、语言和工具,并以Java领域本体库的构建为例详细阐述了本体的构建过程。     

Fast and effective color-based object tracking by boosted color distribution

In this paper, we propose a novel tracking algorithm, boosted color distribution (BCD), for tracking color objects. There exist three contributions in this paper. First, we propose a novel online gentle boost (OGB) algorithm for online learning. The essential idea of OGB is composed of two aspects: online updating candidate weak classifiers, and then choosing and combining them in a boosting way. Second, we design a novel weak classifier, log color feature distribution ratio, which focuses on the difference of color distributions rather than individual samples and provides a simple yet effective manner of mining color features for object tracking. Third, by combining our OGB algorithm and our log color features, we develop a fast yet effective color-based object tracking algorithm. Numerous experiments demonstrate that our tracking algorithm is better than or not worse than some state-of-the-art tracking algorithms on some public sequences.Overall, this paper presents a novel BCD algorithm for color object tracking that achieves good results at a fast speed.     

计算机组装课的发展性评价

在现今我国的计算机领域的高等教育教学和职业技术教学中,有关计算机组装、维护的课程显得尤为重要,而如何的开展好这门课程一直是广大的教育工作者们关注的主要问题.     

浅析数据库数据模型及信息检索方法

本文介绍了多媒体数据库三种主要的数据模型,分析了多媒体信息的特点及对数据模型的特殊要求,论述了不同数据模型的实现途径,并提出了基于内容的信息检索的特点、体系结构和处理方法。     

A Local Semi-Implicit Level-Set Method for Interface Motion

This paper proposes and implements a novel hybrid level set method which combines the numerical efficiency of the local level set approach with the temporal stability afforded by a semi-implicit technique. By introducing an extraction/insertion algorithm into the local level set approach, we can accurately capture complicated behaviors such as interface separation and coalescence. This technique solves a well known problem when treating a semi-implicit system with spectral methods, where spurious interface movements emerge when two interfaces are close to each other. Numerical experiments show that the proposed method is stable, efficient and scales up well into three dimensional problems.     

Global robust output regulation of lower triangular systems with unknown control direction

This paper presents the solvability conditions for the global robust output regulation problem for lower triangular nonlinear systems assuming the control direction is unknown. The approach used is an integration of the robust stabilization technique and Nussbaum gain technique.     

基于区块链的物联网信息安全技术研究

物联网的发展在这几年获得的成果非常明显,在实现智能化管理与操作的同时,存在的隐私安全以及漏洞问题也暴露出来。物联网规模非常庞大,并且还具有分散的拓扑结构。传统的安全与隐私保护方式具有局限性,对于现阶段的物联网操作系统并没有太大的作用。因此,为了保障物联网信息的安全性,弥补传统防护技术上的缺陷,物联网信息防护技术的研究迫在眉睫。     

A Survey on Long-Tailed Visual Recognition

The heavy reliance on data is one of the major reasons that currently limit the development of deep learning. Data quality directly dominates the effect of deep learning models, and the long-tailed distribution is one of the factors affecting data quality. The long-tailed phenomenon is prevalent due to the prevalence of power law in nature. In this case, the performance of deep learning models is often dominated by the head classes while the learning of the tail classes is severely underdeveloped. In order to learn adequately for all classes, many researchers have studied and preliminarily addressed the long-tailed problem. In this survey, we focus on the problems caused by long-tailed data distribution, sort out the representative long-tailed visual recognition datasets and summarize some mainstream long-tailed studies. Specifically, we summarize these studies into ten categories from the perspective of representation learning, and outline the highlights and limitations of each category. Besides, we have studied four quantitative metrics for evaluating the imbalance, and suggest using the Gini coefficient to evaluate the long-tailedness of a dataset. Based on the Gini coefficient, we quantitatively study 20 widely-used and large-scale visual datasets proposed in the last decade, and find that the long-tailed phenomenon is widespread and has not been fully studied. Finally, we provide several future directions for the development of long-tailed learning to provide more ideas for readers.

     

Analysis of Internet Financial Risks Based on Deep Learning and BP Neural Network

Computational Economics - The study aims to analyze and forecast Internet financial risks based on the model based on deep learning and the Back Propagation Neural Network (BPNN). First, the theory...