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很好的边缘检测源代码,使用vc++6.0编写,主要用于医学图像的边缘检测...

于 2023-08-22 发布 文件大小:106.69 kB
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很好的边缘检测源代码,使用vc++6.0编写,主要用于医学图像的边缘检测-good source edge detection, the use of vc 6.0 preparation, mainly for Medical Image Edge Detection

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  • The system is extremely easy to use, even if you have to various network model i...
    该系统使用极其简便,即使 你对各种网络模型不是很深刻的了解,也可以很好的使用该系统。使用时, 你可以自己修改网络的各种参数,交互性较好,而且该系统通过大量的图示 及参数设置,可以让你了解每个应用实例实现的过程及详细步骤。-The system is extremely easy to use, even if you have to various network model is not very profound understanding can be a good use of the system. When used, you can change the network"s own parameters, interactive better, but the system through a lot of icon and parameter settings, so you can understand each application process and the realization of detailed steps.
    2022-03-24 00:57:11下载
    积分:1
  • 神经网络模式识别及其实现,第三章。为大家提供参考。
    神经网络模式识别及其实现,第三章。为大家提供参考。-pattern recognition and neural network to achieve, the third chapter. To provide a reference.
    2022-03-02 01:19:20下载
    积分:1
  • 用BP神经网络程序模拟销售预测,能对销售数据进行时间序列预测,采用VC实现...
    用BP神经网络程序模拟销售预测,能对销售数据进行时间序列预测,采用VC实现-BP neural network simulation sales forecasts, sales data can be right for time series prediction, using VC
    2022-01-26 05:28:06下载
    积分:1
  • ai 代码的C++实现,在VC6.0下运行通过
    ai 代码的C++实现,在VC6.0下运行通过-ai code of C++ to achieve,vc++ Running through
    2022-01-31 10:01:52下载
    积分:1
  • TSP算法,应用局部搜索法得到最优路径,已经经过优化。没有密码,可以使用,vc环境下使用。
    TSP算法,应用局部搜索法得到最优路径,已经经过优化。没有密码,可以使用,vc环境下使用。-TSP algorithm, using local search to be optimal path has been optimized. No password can be used, vc environments.
    2023-07-07 22:15:02下载
    积分:1
  • 学习排序问题的一种方法是将问题转化为分类问题。
    Learning to Rank的一个方法,把排序问题转换成了一个分类问题,然后用支持向量机(SVM)训练出一个模型来。-Learning to Rank of a way to sort problem is transformed into a classification problem, and then use support vector machine (SVM) to train a model.
    2022-12-17 05:40:03下载
    积分:1
  • 用java编写的bp网络和rbf网络的源程序 JNNT由java语言写成,具有跨平台的优越性能.java applet的演示版更简单到只需要任何机器上的浏览...
    用java编写的bp网络和rbf网络的源程序 JNNT由java语言写成,具有跨平台的优越性能.java applet的演示版更简单到只需要任何机器上的浏览器就可以运行,无需安装任何大型附加软件。更方便爱好者通过internet远程访问资源。 -with java bp prepared by the network and the networks of the source rbf JNNT by java language, cross-platform advantages can be. java applet demo version of a more simple to just any machine on the View All can be run without having to install any additional software major. Lovers more convenient remote access through the internet resources.
    2022-03-06 00:56:58下载
    积分:1
  • 这是一本详细介绍遗传算法理论,及其在工程方面应用的书籍,书中包含许多实例,实在是不可多得的经典之书...
    这是一本详细介绍遗传算法理论,及其在工程方面应用的书籍,书中包含许多实例,实在是不可多得的经典之书-This is a detailed theory of genetic algorithm and its applications in engineering books, the book contains many examples, it is rare classic book
    2022-08-17 20:12:47下载
    积分:1
  • 支持向量机的最新的工作工具,它将是非常方便的。
    最新的支持向量机工具箱,有了它会很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, "The Nature of Statistical Learning Theory", Springer-Verlag, New York, ISBN 0-387-94559-8, 1995. [2] J. C. Platt, "Fast training of support vector machines using sequential minimal optimization", in Advances in Kernel Methods - Support Vector Learning, (Eds) B. Scholkopf, C. Burges, and A. J. Smola, MIT Press, Cambridge, Massachusetts, chapter 12, pp 185-208, 1999. [3] T. Joachims, "Estimating the Generalization Performance of a SVM Efficiently", LS-8 Report 25, Universitat Dortmund, Fachbereich Informatik, 1999. -The newest work tools of svm,it will be very convenient to have it.
    2023-08-17 13:35:03下载
    积分:1
  • 落煤残存瓦斯量的确定是采掘工作面瓦斯涌出量预测的重要环节,它直接影响着采掘工作面瓦斯涌出量预测的精度,并与煤的变质程度、落煤粒度、原始瓦斯含量、暴露时间等影响因...
    落煤残存瓦斯量的确定是采掘工作面瓦斯涌出量预测的重要环节,它直接影响着采掘工作面瓦斯涌出量预测的精度,并与煤的变质程度、落煤粒度、原始瓦斯含量、暴露时间等影响因素呈非线性关系。人工神经网络具有表示任意非线性关系和学习的能力,是解决复杂非线性、不确定性和时变性问题的新思想和新方法。基于此,作者提出自适应神经网络的落煤残存瓦斯量预测模型,并结合不同矿井落煤残存瓦斯量的实际测定结果进行验证研究。结果表明,自适应调整权值的变步长BP神经网络模型预测精度高,收敛速度快 该预测模型的应用可为采掘工作面瓦斯涌出量的动态预测提供可靠的基础数据,为采掘工作面落煤残存瓦斯量的确定提出了一种全新的方法和思路。-charged residual coal gas is to determine the volume of mining gas emission rate forecast an important link, which directly affect mining gas emission rate forecast accuracy, and with coal metamorphism, loading coal particle size, the original gas content, exposure time and other factors nonlinear relationship. Artificial neural networks have expressed arbitrary nonlinear relationships and the ability to solve complex nonlinear, time-varying uncertainty and the new ideas and new approaches. Based on this, the author of adaptive neural network loading coal residual gas production forecast model, and a combination of different loading coal mine gas remnants of the actual test results of research
    2022-03-12 11:40:03下载
    积分:1
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