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Snakes_Active_Contour_models_Image_Process_GVF
- 图像处理的关于Snakes : Active Contour Models算法和水平集以及GVF的几篇文章，文章列表为： [1]Snakes Active Contour Models.pdf [2]Multiscale Active Contours.pdf [3]Snakes, shapes, and gradient vector flow.pdf [4]Motion of level sets by mean curvature I.pdf [5]Spectral S
LGIF
- 这是“Active contours driven by local and global intensity fitting energy with application to brain MR image segmentation”（简称LGIF模型）的MATLAB源代码。LGIF模型是非常重要局部区域活动轮廓模型, 它结合了CV模型和LBF模型各自的优点。-This is the "Active contours driven by local and global inten
LCV 局部区域活动轮廓模型
- 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 MATLA
bsb
- Hugh Pasika在1997年基于matlab平台开发的BSB网络函数 反馈型神经网络：盒中脑（BSB）模型的matlab实现-Hugh Pasika in 1997 to develop a platform based on the matlab function BSB network feedback-based neural network: the brain box (BSB) model to achieve matlab
ART1
- 人工智能自适应共振理论的运用，脑模型的稳定性，可塑性示范-The use of adaptive resonance theory artificial intelligence, brain model of stability, plasticity model
1
- 同人类任何语言一样，Java为我们提供了一种表达思想的方式。如操作得当，同其他方式相比，随着问题变得愈大和愈复杂，这种表达方式的方便性和灵活性会显露无遗。 不可将Java简单想象成一系列特性的集合；如孤立地看，有些特性是没有任何意义的。只有在考虑“设计”、而非考虑简单的编码时，才可真正体会到Java的强大。为了按这种方式理解Java，首先必须掌握它与编程的一些基本概念。本书讨论了编程问题、它们为何会成为问题以及Java用以解决它们的方法。所以，我对每一章的解释都建立在如何用语言解决一种特定类
Segmentation
- It is a matlab code for detecting brain tumor in MR images using CIELAB color space model segmentation.
PCA_classifier
- A basic PCA classifier is provided here for a two class classification problem. An example is given, with some multimodal MRI scans from Multiple Sclerosis patients, in which the brain lesions of two patients are annotated and in the third are dete
691609664cmac
- 小脑神经关节控制模型，示例程序，小脑神经关节控制模型-Joint control of small brain model, sample program, the joint control of small model of brain
Thinking_In_Java
- 贯穿本书，在您的大脑里建立一个模型——或者说一个“知识结构”。这样可加深对语言的理解(JAVA编程思想)-Throughout the book, in your brain to create a model- or a " knowledge structure." This will deepen the understanding of language (JAVA programming ideas)
LBF
- 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 mod
skull.raw
- 三维重建中的骨头模型，文件格式为RAW，-Three-dimensional reconstruction of the brain model, RAW file format
NN_code
- 為了在語音及影像辨認獲至與人腦相似的功能，自1940年起，科學家即著手從事此方面的研究，仿造最簡單的神經元模式，開始建立最原始的類神經網路(Artificial Neural Network ANN)，歷經40年的發展，類神經的研究工作雖曾一度陷入低潮，近幾年又再度復甦，並且結合了生理，心理，電腦等科技而成為新的研究領域。-Voice and image recognition in order to be similar to the function of the human brain,
GPU-CUDA001
- 文章介绍如何使用CUDA实现神经网络，并把他应用在GPU图像处理单元上。 -An Artificial Neural Network is an information processing method that was inspired by the way biological nervous systems function, such as the brain, to process information. It is composed of a large number of
MR-image-segmentation
- 对MR脑肿瘤图像进行分割,并对分割的结果进行矩描述。方法 在分析当前常用的医学图像分割方法 的基础上,提出一种基于形变模型的医学图像分割方法,并给出了相应的理论算法模型和实现步骤,最后用Visual C ++ 6·0编程,并对MR脑肿瘤图像进行分割实验 -MR images of brain tumor segmentation, and segmentation results Moment. Methods used in the analysis of the current
neur271
- 大脑神经网络中的皮层和丘脑模型计算程序，采用HH模型进行计算，可以得出神经元电位发放图。-Brain cortex and thalamus in the network model procedure for the HH model is calculated potential distribution of neurons can be drawn map.
ganzhi
- 感知准则函数是五十年代由Rosenblatt提出的一种自学习判别函数生成方法，Rosenblatt企图将其用于脑模型感知器，因此被称为感知准则函数。其特点是随意确定的判别函数初始值，在对样本分类训练过程中逐步修正直至最终确定。 -Perception criterion function is the 1950s proposed by Rosenblatt, a self-learning discriminant function generation method, Rosenblat
Cognitive-Radio-Brain-Empowered
- Simon Haykin的基于脑模型的认知无线通讯-Simon Haykin，brain-based model of cognitive wireless communication
brain
- model 3d of a humen bran , on 3d ma extension .3ds
ConCog08
- 一篇很好的文章，此文章关于大脑皮层神经元做了详细的描述，很有参考价值。(This paper presents a computer model of cortical broadcast and competition based on spiking neurons and inspired by the hypothesis of a global neuronal workspace underlying conscious information processing in the