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Description: 针对现有遗传算法在多维非线性优选方面的不足，本文提出了一种基于小生境进化算法（NEA）的非线性优选模型，探讨了NEA算法的参数选择原则。通过大量仿真和比较，表明算法在复杂非线性优选中具有快速、高效、鲁棒性强的特点，并能在全局范围内有效搜索所有最优解。
-against existing genetic algorithms in three-dimensional nonlinear optimization for the shortage, the paper presents a niche evolutionary algorithm (NEA) nonlinear optimization model, the NEA on the parameters chosen algorithm principle. Through simulation and large, the algorithm shown in a complex nonlinear optimization is fast, efficient, robust features of the strong, and the global scope effective search all the optimal solution.
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Size: 38027 |
Author: 黄善理 |
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Description: SURF spped up robust features openCV 实现
为源代码 Fast SIFT
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Size: 683177 |
Author: hu |
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Description: 《Robust features for noisy speech recognition based on filtering and spectral peaks in autocorrelation domain》语音识别的鲁棒性方面的英文资料
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Size: 235193 |
Author: 付诗 |
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Description: 针对现有遗传算法在多维非线性优选方面的不足，本文提出了一种基于小生境进化算法（NEA）的非线性优选模型，探讨了NEA算法的参数选择原则。通过大量仿真和比较，表明算法在复杂非线性优选中具有快速、高效、鲁棒性强的特点，并能在全局范围内有效搜索所有最优解。
-against existing genetic algorithms in three-dimensional nonlinear optimization for the shortage, the paper presents a niche evolutionary algorithm (NEA) nonlinear optimization model, the NEA on the parameters chosen algorithm principle. Through simulation and large, the algorithm shown in a complex nonlinear optimization is fast, efficient, robust features of the strong, and the global scope effective search all the optimal solution.
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Size: 37888 |
Author: 黄善理 |
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Description: A general technique for the recovery of signi cant
image features is presented. The technique is based on
the mean shift algorithm, a simple nonparametric pro-
cedure for estimating density gradients. Drawbacks of
the current methods (including robust clustering) are
avoided. Feature space of any nature can be processed,
and as an example, color image segmentation is dis-
cussed. The segmentation is completely autonomous,
only its class is chosen by the user. Thus, the same
program can produce a high quality edge image, or pro-
vide, by extracting all the signi cant colors, a prepro-
cessor for content-based query systems. A 512 512
color image is analyzed in less than 10 seconds on a
standard workstation. Gray level images are handled
as color images having only the lightness coordinate-A general technique for the recovery of sig ni cannot image features is presented. The techni que is based on the mean shift algorithm, a simple nonparametric pro-cedure for estimat ing density gradients. Drawbacks of the curren t methods (including robust clustering) are av oided. Feature space of any nature can be proces sed, and as an example, color image segmentation is dis-cussed. The se gmentation is completely autonomous. only its class is chosen by the user. Thus, the same program can produce a high quality edge image, or pro-vide. by extracting all the signi cannot colors, a prepro- cessor for content-based query syste ms. A 512,512 color image is analyzed in less than 10 seconds on a standard workstation. Gray 4ISR l images are handled as color images having only the lightness c
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Size: 17408 |
Author: gggg |
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Description: SURF spped up robust features openCV 实现
为源代码 Fast SIFT-SURF spped up robust features openCV the realization of the source code for the Fast SIFT
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Size: 683008 |
Author: hu |
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Description: 本源码是利用视觉仿生学成果进行目标识别的最新成果。c1 c2特征是MIT的Poggio教授的研究小组根据人眼视觉仿生的研究成果提出的特征。运用该特征对自然图像中的目标识别取得了较好的效果。本压缩包为提取C1 C2特征的Matlab源码。C1 C2特征的详细说明参见IEEE PAMI 2007上的文献"Robust Object Recognition with Cortex-Like Mechanisms"。-The source is the use of visual object recognition bionics results of the latest achievements. c1 c2 characterized by MIT Professor of Poggio research team in accordance with human visual biomimetic study the characteristics of the results. Use of the characteristics of the natural image object recognition has achieved good results. The compressed packet to extract the characteristics of C1 C2 source Matlab. C1 C2 features a detailed description see the IEEE PAMI 2007 literature Robust Object Recognition with Cortex-Like Mechanisms .
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Size: 16384 |
Author: csb |
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Description: 《Robust features for noisy speech recognition based on filtering and spectral peaks in autocorrelation domain》语音识别的鲁棒性方面的英文资料- Robust features for noisy speech recognition based on filtering and spectral peaks in autocorrelation domain Robust Speech Recognition sexual information in English
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Size: 234496 |
Author: 付诗 |
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Description: 模拟人的思维特点,提出一种新型智能控制器:仿人逻辑预测控制器. 该控制器融合了基于泛布尔代数的逻辑控制器和基于模型的预测控制器的特点, 是一种多值逻辑混合动态系统. Matlab仿真表明, 该控制器在模型匹配时性能良好, 在模型失配时依然能满意运行, 表现出鲁棒性强, 超调量小的特点. 与其它类型人工智能控制器相比, 该控制器结构简单, 物理背景明确, 数学概念清晰, 便于在工业控制领域推广应用.-Simulation of the characteristics of people' s thinking, a new intelligent controller: humanoid logic controller prediction. The controller is based on the integration of pan-Boolean algebra of logic controllers and model-based predictive controller features, is a multi-valued logic hybrid dynamic systems. Matlab simulation show that the controller performance in the model match well when the model mismatch can be satisfied with the operation still showed robust, ultra-tune the characteristics of a small amount. with other types of artificial intelligence controller ratio, the controller structure is simple and clear physical background, the concept of math clear, easy in the field of industrial control application.
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Size: 267264 |
Author: 文豪 |
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Description: SURF (Speeded Up Robust Features)
http://en.wikipedia.org/wiki/SURF
测试了很多surf的源代码 这个带有匹配的演示例子很不错-code from： http://code.google.com/p/opensurf1/downloads/list
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Size: 118784 |
Author: linlin |
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Description: Our toolbox currently contains implementations of robust methods for
location and scale estimation, covariance estimation (FAST-MCD), regression (FAST-
LTS, MCD-regression), principal component analysis (RAPCA, ROBPCA), princi-
pal component regression (RPCR), partial least squares (RSIMPLS) and classi¯ cation
(RDA). Only a few of these methods will be highlighted in this paper. The toolbox
also provides many graphical tools to detect and classify the outliers. The use of these
features will be explained and demonstrated through the analysis of some real data
sets.
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Author: 王一 |
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Description: A very fast and robust object detection
framework.
A very simple set of Haar like box features
A commensurating Image representation (that
enables fast calculation of features, feature
scaling and normalization)
Efficient feature selection based on boosting
Attentional Cascading of classifiers that spends
more time on promising regions.
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Size: 161792 |
Author: jinwoosmile |
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Description: ExtractSURF
Extracts Speeded Up Robust Features from image. downlæ oad and install opencv 1.1pre-ExtractSURF
Extracts Speeded Up Robust Features from image. downlæ oad and install opencv 1.1pre
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Size: 1024 |
Author: rahman |
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Description: Speeded Up Robust Features 在SIFT特正点匹配算法上进行改进，代码已完成Matlab->VC的程序打包-Speeded Up Robust Features in the SIFT matching algorithm special on-time improvement, the code has been completed Matlab-> VC packing process
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Size: 1154048 |
Author: 萧峙清 |
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Description: In this paper, a novel scale- and rotation-invariant interest point detector and descriptor, coined SURF (Speeded Up Robust
Features) is presented. It approximates or even outperforms previously proposed
schemes with respect to repeatability, distinctiveness, and robustness, yet
can be computed and compared much faster.
This is achieved by relying on integral images for image convolutions by building on the strengths of the leading existing detectors and descriptors (in casu, using a Hessian matrix-based measure for the detector, and a
distribution-based descriptor) and by simplifying these methods to the
essential. This leads to a combination of novel detection, description, and
matching steps. The paper presents experimental results on a standard
evaluation set, as well as on imagery obtained in the context of a real-life
object recognition application. Both show SURF’s strong performance.-In this paper, a novel scale- and rotation-invariant interest point detector and descriptor, coined SURF (Speeded Up Robust
Features) is presented. It approximates or even outperforms previously proposed
schemes with respect to repeatability, distinctiveness, and robustness, yet
can be computed and compared much faster.
This is achieved by relying on integral images for image convolutions by building on the strengths of the leading existing detectors and descriptors (in casu, using a Hessian matrix-based measure for the detector, and a
distribution-based descriptor) and by simplifying these methods to the
essential. This leads to a combination of novel detection, description, and
matching steps. The paper presents experimental results on a standard
evaluation set, as well as on imagery obtained in the context of a real-life
object recognition application. Both show SURF’s strong performance.
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Size: 686080 |
Author: yangwei |
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Description: GPU Accelerating Speeded-Up Robust Features. Many computer vision tasks require interest point detection and description, such as real-time visual navigation. We present a GPU implementation of the recently proposed Speeded-Up Robust Feature extractor, currently the state of the art for
this task. Robust feature descriptors can give vast improvements
in the quality and speed of subsequent steps, but require intensive
computation up front that is well-suited to inexpensive graphics
hardware. We describe the algorithm’s translation to the GPU in
detail, with several novel optimizations, including a new method
of computing multi-dimensional parallel prefix sums. It operates
at over 30 Hz at HD resolutions with thousands of features and
in excess of 70 Hz at SD resolutions.
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Size: 1541120 |
Author: yangwei |
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Description: SURF: Speeded Up Robust Features
suft算法-SURF: Speeded Up Robust Features suft algorithm
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Size: 680960 |
Author: liqi |
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Description: 讲述了凸优化的基本理论，包括定义，模型，鲁棒特性以及对信号重构的指导等。-Describes the basic theory of convex optimization, including definitions, models, robust features and guidance on the signal reconstruction.
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Size: 14794752 |
Author: 张巧玲 |
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Description: SURF算法，是SIFT的升级版，速度更快，性能也不差，快速实现图像特征点的检测和匹配。-SURF algorithm, is an upgraded version of SIFT, faster, not bad performance, rapid detection of image feature points and matching.
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Size: 1362944 |
Author: 张东兴 |
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Description: surf特征点提取以及相应的特征点匹配，matlab程序-speed up robust features (SURF), feature matching
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Size: 722944 |
Author: david |
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