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深入浅出介绍计算机视觉的最新动态。内容包括：
* Camera calibration using 3D objects, 2D planes, 1D lines, and self-calibration
* Extracting camera motion and scene structure from image sequences
* Robust regression for model fitting using M-estimators, RANSAC, and
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数据分析与统计的相关学习和程序，包括概率和回归分析-Data analysis and statistics related to learning and procedures, including probability and regression analysis, etc.
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支持向量机结构回归算法（svm-struct），一种新的回归方法，有文献和PPT，方便学习。-Support the structural regression algorithm vector machine (svm-struct), a new regression method, literature and PPT to facilitate learning.
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支持向量机回归理论与神经网络等非线性回归理论相比具有许多独特的优点有线性回归和非线性回归,其模型的选 择包括核的选择、容量控制以及损失函数的选择.在控制方面的研究包括非线性 时间序列 的预测及应用、系统辨识以及优化控制和学习控制等方面的研究-Support vector machine (SVM) regression theory and neural network has many unique advantages such as nonlinear regression theory
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Karl Sketting RLS-DL回归最小二乘字典学习算法，可用于超分辨率重建，MATLAB版-Karl Sketting RLS-DL dictionaries least squares regression learning algorithms can be used to super-resolution reconstruction, MATLAB version
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在机器学习领域，支持向量机SVM(Support Vector Machine）是一个有监督的学习模型，通常用来进行模式识别、分类、以及回归分析-In the field of machine learning, support vector machine SVM (Support Vector Machine) is a supervised learning model, typically used for pattern recognition, classification, and
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人脸特征点定位，将深度学习运用到人脸对齐中，卷积神经网络
-Facial features localization, depth learning to use face alignment, the convolutional neural network
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非常有效、高准确率的人脸对齐方法，“显式形状回归”。通过训练数据最小化对齐错误函数，学习一个向量回归函数直接推断整个面部形状（一个特征点集合）-Very efficient and highly accurate face alignment method, explicit shape regression . Through the training data minimization alignment error function, learning a vector regressi
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