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machine learning

  • Semantic analysis of multimedia content is an on going research area that has gained a lot of atten

    Semantic analysis of multimedia content is an on going research area that has gained a lot of attention over the last few years. Additionally, machine learning techniques are widely used for multimedia analysis with great success. This work presents a combined approach to semantic adaptation of neural network classifiers in multimedia framework. It is based on a fuzzy reasoning engine which is able to evaluate the outputs and the confidence levels of the neural network classifier, using a knowledge base. Improved image segmentation results are obtained, which are used for adaptation of the network classifier, further increasing its ability to provide accurate classification of the specific content.

    標簽: multimedia Semantic analysis research

    上傳時間: 2016-11-24

    上傳用戶:蟲蟲蟲蟲蟲蟲

  • pdf格式的英文文獻

    pdf格式的英文文獻,是關于認知無線電網絡的,編者是加拿大桂爾夫大學的Qusay H. Mahmoud。ISBN:978-0-470-06196-1 章節內容: 1 Biologically Inspired Networking 2 The Role of Autonomic Networking in Cognitive Networks 3 Adaptive Networks 4 Self-Managing Networks 5 machine learning for Cognitive Networks: Technology Assessment and Research Challenges 6 Cross-Layer Design and Optimization in Wireless Networks 等,共計13章,全書348頁,pdf文件383頁。

    標簽: 英文

    上傳時間: 2014-01-27

    上傳用戶:daguda

  • Text mining tries to solve the crisis of information overload by combining techniques from data mini

    Text mining tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. In addition to providing an in-depth examination of core text mining and link detection algorithms and operations, this book examines advanced pre-processing techniques, knowledge representation considerations, and visualization approaches. Finally, it explores current real-world, mission-critical applications of text mining and link detection in such varied fields as M&A business intelligence, genomics research and counter-terrorism activities.

    標簽: information techniques combining overload

    上傳時間: 2014-01-02

    上傳用戶:Late_Li

  • 介紹回歸問題中高斯過程的應用

    介紹回歸問題中高斯過程的應用,C. E. Rasmussen & C. K. I. Williams, Gaussian Processes for machine learning,

    標簽: 回歸 高斯 過程

    上傳時間: 2017-07-25

    上傳用戶:skfreeman

  • Pattern Analysis is the process of fi nding general relations in a set of data, and forms the

    Pattern Analysis is the process of fi nding general relations in a set of data, and forms the core of many disciplines, from neural networks to so-called syn- tactical pattern recognition, from statistical pattern recognition to machine learning and data mining. Applications of pattern analysis range from bioin- formatics to document retrieval.

    標簽: the relations Analysis Pattern

    上傳時間: 2017-09-07

    上傳用戶:SimonQQ

  • machine learning in action

    機器學習實戰 英文原版 涵蓋基礎算法的實戰演練和源碼

    標簽: machine learning

    上傳時間: 2015-04-14

    上傳用戶:dyd1123

  • Applications of Evolutionary Computing

    Evolutionary Computation (EC) deals with problem solving, optimization, and machine learning techniques inspired by principles of natural evolution and ge- netics. Just from this basic definition, it is clear that one of the main features of the research community involved in the study of its theory and in its applications is multidisciplinarity. For this reason, EC has been able to draw the attention of an ever-increasing number of researchers and practitioners in several fields.

    標簽: Applications Evolutionary Computing of

    上傳時間: 2020-05-26

    上傳用戶:shancjb

  • Cognitive+Radio+Technology

    This introduction takes a visionary look at ideal cognitive radios (CRs) that inte- grate advanced software-defined radios (SDR) with CR techniques to arrive at radios that learn to help their user using computer vision, high-performance speech understanding, global positioning system (GPS) navigation, sophisticated adaptive networking, adaptive physical layer radio waveforms, and a wide range of machine learning processes.

    標簽: Technology Cognitive Radio

    上傳時間: 2020-05-26

    上傳用戶:shancjb

  • Embedded_Deep_Learning_-_Algorithms

    Although state of the art in many typical machine learning tasks, deep learning algorithmsareverycostly interms ofenergyconsumption,duetotheirlargeamount of required computations and huge model sizes. Because of this, deep learning applications on battery-constrained wearables have only been possible through wireless connections with a resourceful cloud. This setup has several drawbacks. First, there are privacy concerns. Cloud computing requires users to share their raw data—images, video, locations, speech—with a remote system. Most users are not willing to do this. Second, the cloud-setup requires users to be connected all the time, which is unfeasible given current cellular coverage. Furthermore, real-time applications require low latency connections, which cannot be guaranteed using the current communication infrastructure. Finally, wireless connections are very inefficient—requiringtoo much energyper transferredbit for real-time data transfer on energy-constrained platforms.

    標簽: Embedded_Deep_Learning Algorithms

    上傳時間: 2020-06-10

    上傳用戶:shancjb

  • machine learning and IoT

    The present era of research and development is all about interdisciplinary studies attempting to better comprehend and model our understanding of this vast universe. The fields of biology and computer science are no exception. This book discusses some of the innumerable ways in which computational methods can be used to facilitate research in biology and medicine—from storing enormous amounts of biological data to solving complex biological problems and enhancing the treatment of various diseases.

    標簽: Learning Machine IoT and

    上傳時間: 2020-06-10

    上傳用戶:shancjb

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