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自适应的目标识别算法，它包含了当前主要的目标识别算法。-adaptive target recognition algorithm, which includes the current main target recognition algorithm.
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机器人程序，有对象识别，IO控制，图像处理等方面算法-robot procedures, object recognition, IO control, image processing algorithms etc.
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Standard model object recognition matlab code-Standard model object recognition Matlab code
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7类别的 Adaline 神经网络的模式识别程序, 可自行变换或者定义要分类的目标和向量的长度-7 types of Adaline neural network pattern recognition procedures, the definition of self-transformation or to the classification of the object and the length of vector
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针对目标与背景两类图像模式识别问题,在已有的特征选择方法基础上,提出了一种新颖的基于免疫分子编码机理的图像特征选择方法(IACA). 该方法借鉴生物免疫系统的抗体分
子编码机理,在对样本进行参数估计情况下,提出熵度量单个特征对于目标和背景的识别敏感度 从集合的角度研究并且定义了特征之间的包含和互补关系 并且基于组成抗体分子氨基酸结合能量最小原则,提出了关于图像目标的免疫抗体构建规则 最终实现了寻找最优特征子集的算法IACA ,该特征子集的维数通过算法自动获得无需人为设定,选择结果为目标的“免
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：本文较为系统地介绍了纸币面值数字图象识别的计算机仿真。文中详细介绍了模版
匹配、特征点匹配、神经网络等字符识别方法，并进行了比较。根据本文研究对象的特点，选择
了从分析数字本身的拓扑结构入手，根据字符投影分布的规律来判断和识别的方法，成功实现
了纸币面值的识别。-: This article notes a more systematic introduction to digital image recognition, face value of the computer si
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DOT算法,dot of template,用于在线识别物体，尤其是对纹理比较简单的物体的在线检测，效果比较明显，比如玻璃瓶，手机等物体-DOT algorithm, dot of template, for online object recognition, especially for relatively simple objects, the texture of online testing, the effect is more obvious, such as glass bot
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基于dpca的程序，应用于故障检测与故障诊断,还有故障识别，效果很好，对象为csth-Dpca based on the program, used in the fault detection and fault diagnosis, and fault recognition, the effect is very good, for CSTH object
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基于dpca的程序，应用于故障检测与故障诊断,还有故障识别，效果很好，对象为cstr，效果明显-Dpca based on the program, used in the fault detection and fault diagnosis, and fault recognition, the effect is very good, object for CSTR, the effect is obvious
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基于dpca的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为cstr，程序简单-Dpca based on the program, used in the fault detection and fault diagnosis, and fault recognition, identification of the good effect, the object for CSTR, procedure is simple
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基于pca和dpca的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为cstr，程序简单-Based on the pca and dpca program, used in the fault detection and fault diagnosis, and fault recognition, identification of the good effect, the object for CSTR, procedure is simple
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基于pca和dpca以及流形法的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为cstr，程序简单-Based on the pca and dpca and manifold method program, used in the fault detection and fault diagnosis, and fault recognition, identification of the good effect, the object for CSTR, procedu
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基于pca和dpca以及流形法和动态流形发的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为cstr，程序简单-Based on the pca and dpca and manifold method and dynamic manifold hair of program, used in the fault detection and fault diagnosis, and fault recognition, identification of the good e
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基于pca和kpca以及流形法和核流形发的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为cstr，程序简单-Based on the pca and dpca and manifold method and procedure of the nuclear manifold hair, applied to fault detection and fault diagnosis, and fault recognition, identification of the go
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基于kpca以及核流形发的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为cstr，程序简单-Based on kpca and nuclear manifold hair of program, used in the fault detection and fault diagnosis, and fault recognition, identification of the good effect, the object for CSTR, procedure is
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基于kpca以及dpca,核流形发的程序，应用于故障检测与故障诊断,还有故障识别，识别的效果很好，对象为cstr，程序简单-Based on kpca and dpca, nuclear manifold hair of program, used in the fault detection and fault diagnosis, and fault recognition, identification of the good effect, the object for CSTR, pr
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In pattern recognition, the k-nearest neighbor algorithm (k-NN) is a method for classifying objects based on closest training examples in the feature space. k-NN is a type of instance-based learning, or lazy learning where the function is only approx
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Combine detect motion object
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深度学习允许由多个处理层组成的计算模型来学习具有多个抽象层次的数据表示。这些方法极大地提高了语音识别、视觉对象识别、目标检测以及药物发现和基因组学等许多领域的最新进展。深度学习发现复杂的结构在大数据集，通过使用反向传播算法来指示一台机器应该如何改变其内部参数，用于计算在每一层的代表性，从上一层的代表。深层卷积网在处理图像、视频、语音和音频方面取得了突破性进展，而递归网络则在文本和语音等连续数据上起到了作用。(Deep learning allows computational models th
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智能监控平台的网站服务基于Flask开源框架，图像识别与信息提取功能则基于cv2和tensorflow等一系列相关的第三方库。以网页的形式进行人脸识别、目标检测、目标跟踪等，并且可以存储相关的操作记录、用户登录、管理员登录(Intelligent monitoring platform's website service is based on Flask open source framework, while image recognition and information extract
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