微型惯性测量组合包括微型陀螺仪和微型加速度计，是MEMS技术在惯性技术领域成功应用。与传统的惯性器件相比，MIMU在设计、材料和制造等方面都采用了全新的、革命性的工艺和方法，使其具有前所未见的小体积和重量、商业级的低价格、极高的可靠性和寿命。MIMU的这些特点使得惯性测量技术的应用从不计成本的军事领域扩展到市场广阔的民用、商用领域。
Micro inertial measurement units, including micro-gyroscopes and micro-accelerometers, MEMS technology is successfully applied in the field of inertial technology. Compared with the traditional inertial devices, MIMU in design, materials and manufacturing are adopting a new, revolutionary technology and methods, it has the unprecedented small size and weight, commercial-grade, low price high reliability and life. MIMU of these features make the inertial measurement technology from the military in the field regardless of cost to market a vast expansion of civil, commercial area. (2012-05-17, Others, 595KB, 下载11次)
:提出一种基于尺度不变特征变换(SIFT)特征匹配的目标跟踪方法.首先使用SIFT提取目标特征,构
建目标特征库,然后使用基于K维树的特征匹配算法,对实时序列图像提取的SIFT特征与特征库中目标进行精确匹配
: Based on Scale Invariant Feature Transform (SIFT) feature matching target tracking. The first to use SIFT target feature extraction, feature library building goals, and then use the K-dimensional tree based feature matching algorithm for real-time image sequences extracted SIFT features and characteristics of the target database accurately match (2010-04-09, Others, 258KB, 下载91次)
机器学习是人工智能的一个子领域，是人工智能中非常活跃且范围甚广的主要核心研究领域之一，也是现代智能系统的关键环节和瓶颈。机器学习吸取了人工智能、概率统计、计算复杂性理论、控制论、信息论、哲学、生理学、神经生物学等学科的成果，主要关注于开发一些让计算机可以自动学习的技术，并通过经验提高系统自身的性能。本文介绍了机器学习的概念、基本结构和发展，以及各种机器学习方法，包括机械学习、归纳学习、类比学习、解释学习、基于神经网络的学习以及知识发现等，并简单叙述了机器学习的相关算法，包括决策树算法、随机森林算法、人工神经网络算法、SVM算法、Boosting与Bagging算法、关联规则算法、贝叶斯学习算法以及EM算法等，最后还指出了机器学习的应用及其发展趋势。
Machine learning is a subset of the field of Artificial Intelligence,is very active in Artificial Intelligence and a wide range of research in the field of one of the main core, is the key and the bottleneck of a modern intelligent system.Machine Learning has absorbed the results of Artificial Intelligence, Probability and Statistics, Computational Complexity Theory, Cybernetics, Information Theory, Philosophy, Physiology and Neurobiology, and other disciplines.It concerns mainly about how to develop some of technology which can make the computer auto-learning,and through experiences to improve the performance of the system itself.This paper introduces the concept,the basic structure and development of machine learning, and a variety of machine learning methods,including machine learning, inductive learning, learning by analogy, explanation-based learning,based on neural network learning and knowledge discovery, and so on. And briefly descrip the algorithms of machine learning,includin (2009-06-13, Others, 32KB, 下载43次)
人工智能(Artificial Intelligence，AI)一直都处于计算机技术的最前沿，经历了几起几落…… 长久以来，人工智能对于普通人来说是那样的可望而不可及，然而它却吸引了无数研究人员为之奉献才智，从美国的麻省理工学院(MIT)、卡内基-梅隆大学(CMU)到IBM公司，再到日本的本田公司、SONY公司以及国内的清华大学、中科院等科研院所，全世界的实验室都在进行着AI技术的实验。不久前，著名导演斯蒂文斯皮尔伯格还将这一主题搬上了银幕，科幻片《人工智能》(A.I.)对许多人的头脑又一次产生了震动，引起了一些人士了解并探索人工智能领域的兴趣。
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