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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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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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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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