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[Special Effectsjiqishijue

Description: 机器视觉,计算机视觉,人脸识别,形态学,图像采集,压缩编码,数字水印,神经网络,人工智能,模式识别,特征提取,图像检索,视频检索,计算机图形学-machine vision, computer vision, face recognition, morphology, image acquisition, compression, digital watermarking, neural network, artificial intelligence, pattern recognition, feature extraction, image retrieval, video retrieval, computer graphics
Platform: | Size: 323409 | Author: 和上 | Hits:

[Other resourcesom349

Description: 自组织 Kohonen 映射程序,当一个神经网络接受外界输入模式时,将会分为不同的区域,各区域对输入模式具有不同的响应特征,同时这一过程是自动完成的。各神经元的连接权值具有一定的分布。最邻近的神经元互相刺激,而较远的神经元则相互抑制,更远一些的则具有较弱的刺激作用。自组织特征映射法是一种无教师的聚类方法。 -Kohonen self-organizing map process, when a neural network to outside input mode, will be divided into different regions, the regional input to the model with different response characteristics and the process is done automatically. The neurons connect with the right to a certain value of the distribution. Most neighboring neurons stimulate each other, distant neurons were mutual inhibition, the vision has a weaker stimulus. Self-organizing feature mapping method is a non-teachers clustering method.
Platform: | Size: 3700 | Author: yybb | Hits:

[Other resource自组织特征映射应用实例

Description: 开发环境:Matlab 简要说明:自组织特征映射模型(Self-Organizing feature Map),认为一个神经网络接受外界输入模式时,将会分为不同的区域,各区域对输入模式具有不同的响应特征,同时这一过程是自动完成的。各神经元的连接权值具有一定的分布。最邻近的神经元互相刺激,而较远的神经元则相互抑制,更远一些的则具有较弱的刺激作用。自组织特征映射法是一种无教师的聚类方法。-development environment : Matlab Brief Description : Self-Organizing Map model (Self-Organizing Map feature), a neural network that external input mode, will be divided into different regions, the regional input to the model with different response characteristics and the process is automatic End %. The neurons connect with the right to a certain value of the distribution. Most neighboring neurons stimulate each other, distant neurons were mutual inhibition, the vision has a weaker stimulus. Self-organizing feature mapping method is a non-teachers clustering method.
Platform: | Size: 731 | Author: 李洋 | Hits:

[Bio-Recognizesj10

Description: 基于机器视觉的嘴巴状态检测方法:利用BP神经网络-based machine vision mouth State Detection Methods : Artificial Neural Network
Platform: | Size: 110545 | Author: 许奕强 | Hits:

[AI-NN-PRCPN

Description: Counterpropagation Network Vision 源码, 经典的CPN人工神经网络例子源码-Counterpropagation Network Vision Source, a classic example of artificial neural network CPN-source
Platform: | Size: 31744 | Author: | Hits:

[AI-NN-PRsom349

Description: 自组织 Kohonen 映射程序,当一个神经网络接受外界输入模式时,将会分为不同的区域,各区域对输入模式具有不同的响应特征,同时这一过程是自动完成的。各神经元的连接权值具有一定的分布。最邻近的神经元互相刺激,而较远的神经元则相互抑制,更远一些的则具有较弱的刺激作用。自组织特征映射法是一种无教师的聚类方法。 -Kohonen self-organizing map process, when a neural network to outside input mode, will be divided into different regions, the regional input to the model with different response characteristics and the process is done automatically. The neurons connect with the right to a certain value of the distribution. Most neighboring neurons stimulate each other, distant neurons were mutual inhibition, the vision has a weaker stimulus. Self-organizing feature mapping method is a non-teachers clustering method.
Platform: | Size: 4096 | Author: yybb | Hits:

[AI-NN-PR自组织特征映射应用实例

Description: 开发环境:Matlab 简要说明:自组织特征映射模型(Self-Organizing feature Map),认为一个神经网络接受外界输入模式时,将会分为不同的区域,各区域对输入模式具有不同的响应特征,同时这一过程是自动完成的。各神经元的连接权值具有一定的分布。最邻近的神经元互相刺激,而较远的神经元则相互抑制,更远一些的则具有较弱的刺激作用。自组织特征映射法是一种无教师的聚类方法。-development environment : Matlab Brief Description : Self-Organizing Map model (Self-Organizing Map feature), a neural network that external input mode, will be divided into different regions, the regional input to the model with different response characteristics and the process is automatic End %. The neurons connect with the right to a certain value of the distribution. Most neighboring neurons stimulate each other, distant neurons were mutual inhibition, the vision has a weaker stimulus. Self-organizing feature mapping method is a non-teachers clustering method.
Platform: | Size: 1024 | Author: 李洋 | Hits:

[Bio-Recognizesj10

Description: 基于机器视觉的嘴巴状态检测方法:利用BP神经网络-based machine vision mouth State Detection Methods : Artificial Neural Network
Platform: | Size: 110592 | Author: 许奕强 | Hits:

[Special Effectsjiqishijue

Description: 机器视觉,计算机视觉,人脸识别,形态学,图像采集,压缩编码,数字水印,神经网络,人工智能,模式识别,特征提取,图像检索,视频检索,计算机图形学-machine vision, computer vision, face recognition, morphology, image acquisition, compression, digital watermarking, neural network, artificial intelligence, pattern recognition, feature extraction, image retrieval, video retrieval, computer graphics
Platform: | Size: 323584 | Author: 和上 | Hits:

[DocumentsAOI_paper1

Description: Using Neural Network for Computer Vision Inspection of Printed Circuit Board
Platform: | Size: 669696 | Author: li | Hits:

[Special EffectsFeatureextractionforcomputervisionbasedfiredetecti

Description: 火灾视觉特征的提取是视觉火灾探测中的关键问题. 我们主要研究色彩、纹理以及轮廓脉动 等特征的提取,并提出一种度量轮廓脉动信息的距离模型,该模型在规格化的傅立叶描述子空间能 够准确地度量这种时空闪烁特征. 实验结果表明,该方法具有比较好的鲁棒性,有助于提高视觉火 灾探测的准确率、降低误报漏报率.-Based on investigating color , text ure and temporal feat ures for vision based fire detection , a distance model of contour fluct uation between two successive f rames in t he normalized Fourier descriptor s domain was presented to measure t his time varying contour fluct uation feat ure of flame. The model of contour fluct uation is effective and robust for fire recognition. To f urt her reduce fal se alarms , several features ext racted according to color , text ure and the distance model were toget her regarded as a joint feature vector for artificial neural network to detect fire. Experiment s show t hat the algorithm is effective and robust , and t hat it is significant for improving accuracy and reducing fal se alarms.
Platform: | Size: 819200 | Author: 陈卿 | Hits:

[Special Effectsrice_detection

Description: 利用机器视觉系统代替人眼获取各项大米参数,再参照国标对其进行等级划分。在此基础上, 利用MATLAB软件的神经网络工具箱在数理统计基础上完成检测模型的构建,从而实现对未知大米外特性的评判,并为检测大米综合品质奠定了基础。-rice detection.At p resent, the evaluation method of the rice quality in China is still at the level of naked eye observation. How to classify different varieties of rice through the quality parameters based on the adop ted evaluation criteria becomes a new research top ic. In this paper, the machine vision- based method is used in studying the rice quality. On the basis of the evaluation criteria, different kinds of rice are classified. And according to the usage of neural network, the detec2 tion model is established, so it can lay the foundation for the p rediction of the unknown kinds of rice in the future.
Platform: | Size: 8192 | Author: wangjianshe | Hits:

[Special Effectschapter4

Description: 《数字图像处理与机器视觉:Visual C++与Matlab实现》4 特征提取,图像识别初步,人工神经网络,基于ANN的数字字符识别系统-" Digital image processing and machine vision: Visual C++ and Matlab to achieve" four feature extraction, image recognition initially, artificial neural network, ANN based digital character recognition system
Platform: | Size: 726016 | Author: 陈新秋 | Hits:

[Special Effectsfun_pcnn

Description: 基于PCNN的特征提取,PCNN用于特征提取时,具体平移、旋转、尺度、扭曲等不变性,这正是许多年来基于内容的图像检索系统追求的目标,同时PCNN用于特征提取时,有很好的抗噪性。而且PCNN直接来自于哺乳动物视觉皮层神经的研究,具有提取图像形状,纹理,边缘的属性。用PCNN能很好地对图像进行签名,将二维的图像的特征提取成一维矢量签名。-Feature extraction of specified object is an important preprocessing stage in machine vision systems. In this paper, we present a novel hybrid feature extraction method using PCNN (Pulse Coupled Neural Network) and shape information. First, we use PCNN firing map train to formulate object’s time signature, then we use roundness of each firing map to formulate object’s shape information vector, the final feature matrix we got is combined time signature and roundness. We take correlations as our judge criteria in our experiments. It has been proved that the algorithm is not sensitivity with the rotation, scaling and translation of the object and is a useful method for target recognition applications.
Platform: | Size: 1024 | Author: wangxiaofei | Hits:

[Graph Recognizeshou-shi-shi-bie

Description: 对传感器网络与使用者高效协同工作的问题,本文提出了交互式视觉传感器网络的概念,开发了由视觉模块和控 制及通信模块构成的视觉传感器节点,进而构建了典型的交互式视觉传感器网络系统。本文具体探讨了提升交互式视觉传 感器网络综合性能的几个关键技术方案,包括PC平台和嵌入式平台上的语音交互技术,基于小波神经网络的手势识别技术, 以及视觉与RFID的信息融合技术。在医院环境中的初步应用表明本设计的合理性和实用性。-Demanded by the effective cooperation between the users and the sensor networks,in this work,the au— thors have proposed the concept of interactive vision sensor networks and explored the vision sensor nodes,which comprises the vision module。contr01 and communication module.A typical interactive vision sensor network,based on the vision sensor nodes,has been constructed accordingly.In addition,some key solution schemes for improving the comprehensive interactive abilities were introduced.which have included the voice interface technology based on the PC platform and embedded system platform,the gesture interface technology based on wavelet neural network, as well as the information fusion technique of vision and radio-frequency identification(RFID).Preliminary applica— tion in some hospitals indicates the rationality and practicality of the system design.
Platform: | Size: 630784 | Author: Decheng Yu | Hits:

[Special EffectsCitrus-Fruits-pH-Value-detect

Description: 对机器视觉系统采集 的柑橘图像进行图像裁切、RGB 空间至HSI 空间的转换和差值法去图像背景,用色调H 和饱和度S 为输入,建立小波神经网络柑橘pH 预测模型,无损检测柑橘pH。-Images of citrus fruits from machine vision system were processed by cutting, converting from RGB space to HSI space, removing background by deviation. A wavelet neural network model was constructed to detect pH value of citrus fruits non-destructively, the inputs of the model were image hue H and saturation S.
Platform: | Size: 1221632 | Author: ygliang30 | Hits:

[Graph RecognizeSOFTWELL

Description: 车牌识别源代码是专为从事车牌识别软件产品开发的客户而设计的软件开发包。采用国际领先的计算机视觉和图像处理算法,结合国际领先的神经网络算法,我司车牌识别采用模块的方式提供车牌识别功能的软件。具有高速的识别速度和可信识别正确率,以减轻各开发商的开发成本,提高其竞争力。适用于城市交通管理、超速监控、公路收费、停车场管理、被盗车辆侦破、等应用开发。-License plate recognition source code is designed to be engaged in the license plate recognition software product development customer and design software development kit. Using international leader in computer vision and image processing algorithm, combined with the world s leading neural network algorithm, I Division of license plate recognition using module provided in the form of license plate recognition software. High speed recognition speed and credible recognition correct rate, in order to reduce the development costs for developers, improve their competitiveness. Applied to the city traffic management, overspeed monitoring, highway collects fees, parking management, stolen vehicle detection, application development and other.
Platform: | Size: 2797568 | Author: 王振 | Hits:

[Special Effectscamera-calibration

Description: 本文成功的开发了足球机器人视觉识别系统,首先应用基于LVQ神经网络的颜色识别算法进行指定颜色属性的物体的识别,接着提出小球和机器人小车的识别算法,应用训练收敛后的神经网络进行摄像机隐式标定。-In this paper, the successful development of soccer robot vision recognition system, first applied to identify the properties of the specified color based on the color of objects LVQ neural network recognition algorithm, and then made a small ball and robot car recognition algorithm, the application of neural network training convergence for camera Implicit calibration.
Platform: | Size: 9646080 | Author: yujie | Hits:

[Program docMachine-vision-analysis

Description: 硕士论文,基于机器视觉苹果检测算法的研究。主要内容包括:1、国内外研究现状及进展 2、苹果图像采集与处理 3、苹果大小与形状检测 4、粒子群优化的BP神经网络苹果颜色检测算法 5、遗传算法优化BP神经网络苹果缺陷检测算法 6、苹果检测系统的软件、硬件及界面设计-Research on Apple detection algorithm based on machine vision. The main contents include: 1, the domestic and foreign research present situation and the progress of 2, apple image acquisition and processing 3, the shape and size of Apple detection 4, particle swarm optimization of BP neural network in apple color detection algorithm 5, genetic algorithm optimization BP neural network for Apple defect detection algorithm 6, apple detection system software, hardware and interface design
Platform: | Size: 1119232 | Author: 吕吉方 | Hits:

[DSP programstdnn

Description: Motion recognition has received increasing attention in recent years owing to heightened demand for computer vision in many domains, including the surveillance system, multimodal human computer interface, and trac control system. Most conventional approaches classify the motion recognition task into partial feature extraction and time-domain recognition subtasks. However, the information of motion resides in the space-time domain instead of the time domain or space domain independently, implying that fusing the feature extraction and classi cation in the space and time domains into a single framework is preferred.
Platform: | Size: 910336 | Author: nabill | Hits:
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