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  • Neural Networks with Model Compression

    Series series Computer Science (R0)
    Deep learning has achieved impressive results in image classification, computer vision and natural language processing. To achieve better performance, deeper and wider networks have been designed, which increase the demand for computational resources. The number of floating-point operations (FLOPs) has increased dramatically with larger networks, and this has become an obstacle for convolutional ... Read more

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  • Binary Neural Networks

    Algorithms, Architectures, and Applications

    Series series Multimedia Computing, Communication and Intelligence
    Deep learning has achieved impressive results in image classification, computer vision, and natural language processing. To achieve better performance, deeper and wider networks have been designed, which increase the demand for computational resources. The number of floatingpoint operations (FLOPs) has increased dramatically with larger networks, and this has become an obstacle for convolutional ... Read more

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    This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods ... Read more

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  • Cognitive Radio Communication and Networking

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    The author presents a unified treatment of this highly interdisciplinary topic to help define the notion of cognitive radio. The book begins with addressing issues such as the fundamental system concept and basic mathematical tools such as spectrum sensing and machine learning, before moving on to more advanced concepts and discussions about the future of cognitive radio. From the fundamentals in ... Read more

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  • Sparse Representation, Modeling and Learning in Visual Recognition

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    by Hong Cheng ...
    Series series Computer Science (R0)
    This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation, highlighting the practical application of compressed sensing research in visual recognition and computer vision. Topics and features: describes sparse recovery approaches, ... Read more

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  • Low-Power Computer Vision

    Improve the Efficiency of Artificial Intelligence

    Series series Chapman & Hall/CRC Computer Vision
    Energy efficiency is critical for running computer vision on battery-powered systems, such as mobile phones or UAVs (unmanned aerial vehicles, or drones). This book collects the methods that have won the annual IEEE Low-Power Computer Vision Challenges since 2015. The winners share their solutions and provide insight on how to improve the efficiency of machine learning systems. ... Read more

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  • Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning

    Series series IEEE Press Series on Electromagnetic Wave Theory and Applications
    Advances in Electromagnetics Empowered by Artificial Intelligence and Deep LearningAuthoritative reference on the state of the art in the field with additional coverage of important foundational conceptsAdvances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning presents cutting-edge research advances in the rapidly growing areas in optical and RF electromagnetic device ... Read more

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  • Blind Source Separation

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    A systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studiesThe book presents an overview of Blind Source Separation, a relatively new signal processing method. Due to the multidisciplinary nature of the subject, the book has been written so as to appeal to an audience from very different backgrounds. Basic mathematical skills (e.g. on ... Read more

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  • Mathematical Problems in Data Science

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    Series series Computer Science (R0)
    This book describes current problems in data science and Big Data. Key topics are data classification, Graph Cut, the Laplacian Matrix, Google Page Rank, efficient algorithms, hardness of problems, different types of big data, geometric data structures, topological data processing, and various learning methods. For unsolved problems such as incomplete data relation and reconstruction, the book ... Read more

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  • Synchronization Control of Markovian Complex Neural Networks with Time-varying Delays

    by Junyi Wang, Jun Fu ...
    Series series Engineering (R0)
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  • Robust Adaptive Control for Fractional-Order Systems with Disturbance and Saturation

    Series series Wiley-ASME Press Series
    A treatise on investigating tracking control and synchronization control of fractional-order nonlinear systems with system uncertainties, external disturbance, and input saturationRobust Adaptive Control for Fractional-Order Systems, with Disturbance and Saturation provides the reader with a good understanding on how to achieve tracking control and synchronization control of fractional-order ... Read more

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  • Normalization Techniques in Deep Learning

    by Lei Huang ...
    Series series eBColl Synthesis Collection 11
    This book presents and surveys normalization techniques with a deep analysis in training deep neural networks. In addition, the author provides technical details in designing new normalization methods and network architectures tailored to specific tasks. Normalization methods can improve the training stability, optimization efficiency, and generalization ability of deep neural networks (DNNs) and ... Read more

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