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Advances in Feature Selection for Data and Pattern Recognition 评分:

这是关于特征选择和模式识别的电子书,高清,最新版本,经典著作,英文版

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2018-08-29 上传 大小:9.72MB
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Advances in Feature Selection for Data and Pattern Recognition

This book presents recent developments and research trends in the field of feature selection for data and pattern recognition, highlighting a number of latest advances. The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions, and new applications. Some

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A survey of recent advances in visual feature detection

传统检测算法的综述

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Advances in Neural Networks Computational and Theoretical Issues

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Anomaly Detection as a Service: Challenges, Advances, and Opportunities

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New Contributions in Information Systems and Technologies

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Dictionary Learning in Visual Computing

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Recent years have witnessed a deluge of network data propelled by the emerging online social media, user-generated video contents, and global-scale communi- cations, bringing people into the era of big data. Such network big data holds much critical and valuable information including customer experi

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Sensors, Circuits & Instrumentation Systems

Systems, Signals & Devices is one of the large specializations in electrical engineering, mechanical engineering and computer sciences. It derives input from physics, mathematics and is an indispensable feature of all natural- and life sciences in research and in application. The new series "Advance

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特征选择MCFS算法,来自github

n many data analysis tasks, one is often confronted with very high dimensional data. Feature selection techniques are designed to find the relevant feature subset of the original features which can facilitate clustering, classification and retrieval. The feature selection problem is essentially a c

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Representation Learning A Review and New Perspectives

The success of machine learning algorithms generally depends on data representation, and we hypothesize that this is because different representations can entangle and hide more or less the different explanatory factors of variation behind the data. Although specific domain knowledge can be used to

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Springer-Modern.Multivariate.Statistical.Techniques.Regression.classification.and.manifold.learning.(2008)

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Learning Rich Features from RGB-D Images for Object Detection and Segmentation

In this paper we study the problem of object detection for RGB-D images using semantically rich image and depth features.We pro- pose a new geocentric embedding for depth images that encodes height above ground and angle with gravity for each pixel in addition to the hor- izontal disparity. We demon

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Intelligent and Evolutionary Systems: The 20th Asia Pacific Symposium, IES 2016, Canberra, Australia, November 2016, Proceedings (Proceedings in Adaptation, Learning and Optimization) Over the last two decades the field of Intelligent Systems delivered to human kind significant achievements, while

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该代码是http://blog.csdn.net/qq_29656961/article/details/78155792博客里面的代码,代码里面有要用到的图片资源和音乐资源。

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