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Description: 掌握java.io.swing中容器类的使用方法，如：JFrame、JPanel等； 2．掌握布局管理器的使用方法，如：FlowLayout、BorderLayout等； 3．掌握java.io.swing中组件类的作用，如：菜单、工具栏、按钮等； 4．掌握Java事件驱动程序设计-委托模型的设计方法。-master java.io.swing Vessel type of use, such as : class, JPanel; 2. Master layout manager to use, such as : FlowLayout, BorderLayout; 3. Master java.io.swing Component kind of role, such as : menus, toolbars, buttons, etc.; 4. Master Java event-driven programming-commissioned model of the design method.
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Size: 3970 |
Author: 欧狗 |
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Description: 掌握java.io.swing中容器类的使用方法，如：JFrame、JPanel等； 2．掌握布局管理器的使用方法，如：FlowLayout、BorderLayout等； 3．掌握java.io.swing中组件类的作用，如：菜单、工具栏、按钮等； 4．掌握Java事件驱动程序设计-委托模型的设计方法。-master java.io.swing Vessel type of use, such as : class, JPanel; 2. Master layout manager to use, such as : FlowLayout, BorderLayout; 3. Master java.io.swing Component kind of role, such as : menus, toolbars, buttons, etc.; 4. Master Java event-driven programming-commissioned model of the design method.
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Size: 4096 |
Author: 欧狗 |
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Description: Vessel model for GNC toolbox
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Size: 315392 |
Author: Hai |
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Description: 这是“Implicit Active Contours Driven by Local Binary Fitting Energy”（简称LBF模型）的MATLAB源代码。LBF模型是非常重要局部区域活动轮廓模型，它被广泛使用于各个领域，如MRI大脑图像分割，血管图像分割，图像偏差场纠正。-This is the "Implicit Active Contours Driven by Local Binary Fitting Energy" (referred to as the LBF model) of the MATLAB source code. LBF model is very important to local area active contour model, which is widely used in various fields, such as MRI brain image segmentation, vessel segmentation, image bias field correction.
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Size: 52224 |
Author: erdongchen1985 |
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Description: 这是“An efficientlocalChan–Vesemodelforimagesegmentation”（简称LCV模型）的MATLAB源代码。LCV模型是非常重要局部区域活动轮廓模型，它被广泛使用于各个领域，如MRI大脑图像分割，血管图像分割，图像偏差场纠正。-This is "An efficientlocalChan-Vesemodelforimagesegmentation" (referred to as the LCV model) of the MATLAB source code. LCV model is very important to local area active contour model, which is widely used in various fields, such as MRI brain image segmentation, vessel segmentation, image bias field correction.
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Size: 45056 |
Author: erdongchen1985 |
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Description: 该代码实现了基于水平集的图像边缘检测，此改进模型不仅适用于血管壁的内膜，也适用于外膜的提取。实验证明，此改进的水平集模型具备有效性和可实现性。-This improved model not only applies to the intravascular blood vessel, but also to extract the outer membrane. Experiments show that the improved level set model proposed in this thesis is effective and achievability.
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Size: 431104 |
Author: 吴焕焕 |
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Description: 协同定位是多平台编队中的关键问题之一 是实现无人机~ 舰艇编队等定位控制的基础G 从信息融
合的角度研究了编队协同中的导航定位问题 提出了一种新的协同定位算法G 推导了二维情况下 基于最近邻准
则确定伪测量和相伴误差协方差矩阵的模型G 仿真分析表明 该算法可以稳定地完成己平台运动要素的估计-Co-location is one of the key issues in the formation of multi-platform UAV ~ vessel formation positioning control G from the financial information
Together the perspective in the formation of collaborative navigation and positioning a new co-location algorithm G is derived adjacent quasi-two-dimensional case based on recent
Determine the pseudo-measurements and accompanied by the error covariance matrix of the model G simulation results show that the algorithm can steadily own platform motion elements estimated
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Size: 152576 |
Author: dingwei |
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Description: 建立了一个空间固定曲率和挠率的三维血管模型，并绘制出三维的图像-Created a space for fixed three-dimensional curvature and torsion vessel model, and draws three-dimensional images
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Size: 1024 |
Author: schumacher |
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Description: cybership 2 model supply vessel
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Size: 2048 |
Author: cholew |
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Description: Ansys计算血管的流固耦合模态命令流文件，可采用分层单元，使用局部坐标系，非对称模态提取方法处理模态。-input file of FSI model for blood vessel using Ansys
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Size: 1024 |
Author: lvyang |
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Description: A model based method for retinal blood vessel detection
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Size: 300032 |
Author: javad |
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Description: 视网膜血管检测的Gabor变换和机器学习，教程
本教程将演示如何Gabor变换和广义
的线性模型（GLM）可用于视网膜血管检测
图像。
，我们将尝试检测视网膜血管从
的训练图像，首先，Gabor滤波器与图像卷积。
GLM将使用Gabor变换的图像特征确定
（独立变量）和容器的位置
为结果（因变量）。- Retinal Vessel Detection by Gabor Transform and Machine Learning, a Tutorial
This tutorial will demonstrate how Gabor transforms and generalized
linear model (GLM) can be used for detection of retinal vessels in
images.
Specifically, we will attempt to detect the retinal vessels a
training image , by first, convoluting multiple Gabor filters with the image.
A GLM will be determined using the Gabor transformed images as features
(the independent variables), and the locations of the vessels
as the outcome (the dependent variable).
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Size: 3072 |
Author: kk |
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Description: This is our model of caratoide bifurcation along with our conference paper.
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Size: 3685376 |
Author: cyrus.ahmady |
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Description: 对于一个管道模型的弹性力学模拟，计算形变和应力(For the elastic simulation of a pipe model, calculate the deformation and stress)
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Size: 13676544 |
Author: zxxxxxy |
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