圖像處理的關(guān)于Snakes : Active Contour Models算法和水平集以及GVF的幾篇文章，文章列表為：
[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 Stability of Local Deformations Spectral Stability of Local Deformations.pdf
[6]An active contour model for object tracking using the previous contour.pdf
[7]Volumetric Segmentation of Brain Images Using Parallel Genetic AlgorithmsI.pdf
[8]Segmentation in echocardiographic sequences using shape-based snake model.pdf
[9]Active Contours Without Edges.pdf
學(xué)習(xí)圖像處理的人必看的幾篇文章
C++, although a marvelous language, isn t perfect. Matthew Wilson has been working with it for over a decade, and during that time he has found inherent limitations that require skillful workarounds. In this book, he doesn t just tell you what s wrong with C++, but offers practical techniques and tools for writing code that s more robust, flexible, efficient, and maintainable. He shows you how to tame C++ s complexity, cut through its vast array of paradigms, take back control over your code--and get far better results
This book shows how to design and implement C++ software that is more effective: more likely to behave correctly more robust in the face of exceptions more efficient more portable makes better use of language features adapts to change more gracefully works better in a mixed-language environment is easier to use correctly is harder to use incorrectly. In short, software that s just better.
Abstract
The Lucene Server project is an attempt to extend the Jakarta Lucene tool with server capabilities.
Lucene is a robust Java API that enables you creating indexes from text sources and perform powerful searches on these indexes. With Lucene, creating an index must be done programmatically and there are almost no possibilities of integrating index management in a distributed environment. In other words, out of the box, Lucene is suitable for integrating indexing and searching possibilities in a single application but not for providing index/search services for multiple applications.
The Lucene Server project comes with a Java API that propose the following
make it easy to create indexes in a declarative way by simply providing an XML configuration document.
make it easy to personalize the way Lucene must handle different kind of data sources.
provide services for index management and searching that can be accessed from several applications.
enable batch tasks scheduling.
Analytical constant-modulus algorithm, to separate linear combinations of CM sourcesThe algorithm
is robust in the presence of noise, and is tested on measured data,
collected from an experimental set-up.
clearly explains concepts such as introspection, overriding built-ins, extending Perl s object-oriented model, and testing your code for greater stability.
This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar -xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
HTML Parser is a Java library used to parse HTML in either a linear or nested fashion. Primarily used for transformation or extraction, it features filters, visitors, custom tags and easy to use JavaBeans. It is a fast, robust and well tested package.
Versatile visual servoing without knowledge of true jacobian.pdf cobian matrix estimator.
The Jacobian matrix estimator does not need a priori
knowledge of the kinematic structure and parameters
of the robot system, such as camera and link parameters.
The proposed visual servoing control scheme ensures
the convergence of the image-features to desired
trajectories, by using the estimated Jacobian matrix,
which is proved by the Lyapunov stability theory. To
show the effectiveness of the proposed scheme, simulation
and experimental results are presented.
