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这里是关于图像处理之机器学习方面的资料--AdaBoost，自适应boosting.
非常经典的资料-Here is on image processing of machine learning information- AdaBoost, adaptive boosting. Very classical information
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基于支持向量聚类的多聚焦图像融合算法.
从无监督机器学习角度提出了一种基于SVC(support vector clustering)的图像融合规则,解决了基于
SVM(support vector machine)的融合规则在处理多聚焦图像融合问题时所引起的区域混叠与非平滑过渡问题,进一步提高了融合图像的质量.-Based on support vector clustering algorithm for multi-focus image fusion. Never oversig
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A PhD thesis on Semi-supervised learning with Graphs by Xiaojin Zhu. Focuses on creating graphs, based on a mixture of labeled and unlabeled data (as per the semi-supervised learning paradigm) and using processes on these graphs to propagate in rigo
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Support vector regression has been proposed in a number of image processing tasks including blind
image deconvolution, image denoising and single frame super-resolution. As for other machine learning
methods, the training is slow. In this paper,
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Support vector regression has been proposed in a number of image processing tasks including blind
image deconvolution, image denoising and single frame super-resolution. As for other machine learning
methods, the training is slow. In this paper,
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Support vector regression has been proposed in a number of image processing tasks including blind
image deconvolution, image denoising and single frame super-resolution. As for other machine learning
methods, the training is slow. In this paper,
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Support vector regression has been proposed in a number of image processing tasks including blind
image deconvolution, image denoising and single frame super-resolution. As for other machine learning
methods, the training is slow. In this paper,
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Support vector regression has been proposed in a number of image processing tasks including blind
image deconvolution, image denoising and single frame super-resolution. As for other machine learning
methods, the training is slow. In this paper,
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Support vector regression has been proposed in a number of image processing tasks including blind
image deconvolution, image denoising and single frame super-resolution. As for other machine learning
methods, the training is slow. In this paper,
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Support vector regression has been proposed in a number of image processing tasks including blind
image deconvolution, image denoising and single frame super-resolution. As for other machine learning
methods, the training is slow. In this paper,
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ue to the volume conduction multichannel electroencephalogram (EEG) recordings
give a rather blurred image of brain activity. Therefore spatial filters are
extremely useful in single-trial analysis in order to improve the signal-to-noise
ratio.
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A hybrid approach combining extreme learning machine and sparse representation for image classification
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Face recognition has been one of the most interesting and important research fields in the past two decades. The reasons come the need of automatic recognitions and surveillance systems, the interest in human visual system on face recognition, and th
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Efficient Learning of Image Super-resolution and Compression Artifact Removal with Semi-Local Gaussian Proce-Efficient Learning of Image Super-resolution and Compression Artifact Removal with Semi-Local Gaussian Process
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以极限学习机的图
像分割算法为基础， 在确定了最优参数的基础上， 建立了基于ELM的图像分割算法， 并且通过仿真实验对算法的正确性和
有效性进行了验证， 指出这种算法能够更加快速地完成对图像的分割， 并且图像分割孤立点少， 边缘明显， 同时该算法大
大地缩短了样本的训练时间。-In image segmentation algorithm based on machine learning limit, in determining the optimum parameters ba
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包括数据分析、绘图等等,图像的光流法计算的matlab程序,是机器学习的例程。- Data analysis, plotting, etc., Image optical flow calculation matlab program, Machine learning routines.
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