Hans Knutsson – författare

As policymakers and scholars evaluate possible ways forward in the reform and renewal of public services by governments caught up in a recessionary environment, this book aims to offer something different – a comprehensive analysis of the development of the ‘Scandinavian’ way of modernizing public-sector management. No book has yet provided an inside view of the development and character of New Public Management (NPM) in Scandinavia. Although there is a general perception that there is a clear-cut ‘Scandinavian’ model of public policy and management, this book offers a more nuanced interpretation, illuminating subtle distinctions in political, social and economic context which are significant in identifying receptive contexts for the adoption of modernization policies.Organized into three main themes in the modernization of the welfare state – management, governance and marketization – the contents revolve around unique empirical accounts, revealing distinctive Scandinavian characteristics of reform initiatives. The received wisdom may be a hesitant follower of the UK and the USA. But this book offers an alternative interpretation, revealing an edginess in certain Scandinavian settings, particularly in Sweden, which is a largely unrecognized.Without compromising the welfare state, it may be a bold frontrunner in the development of New Public Management.

Signal Processing for Computer Vision is a unique and thorough treatment of the signal processing aspects of filters and operators for low-level computer vision. Computer vision has progressed considerably over recent years. From methods only applicable to simple images, it has developed to deal with increasingly complex scenes, volumes and time sequences. A substantial part of this book deals with the problem of designing models that can be used for several purposes within computer vision. These partial models have some general properties of invariance generation and generality in model generation. Signal Processing for Computer Vision is the first book to give a unified treatment of representation and filtering of higher order data, such as vectors and tensors in multidimensional space. Included is a systematic organisation for the implementation of complex models in a hierarchical modular structure and novel material on adaptive filtering using tensor data representation. Signal Processing for Computer Vision is intended for final year undergraduate and graduate students as well as engineers and researchers in the field of computer vision and image processing.

As policymakers and scholars evaluate possible ways forward in the reform and renewal of public services by governments caught up in a recessionary environment, this book aims to offer something different – a comprehensive analysis of the development of the ‘Scandinavian’ way of modernizing public-sector management. No book has yet provided an inside view of the development and character of New Public Management (NPM) in Scandinavia. Although there is a general perception that there is a clear-cut ‘Scandinavian’ model of public policy and management, this book offers a more nuanced interpretation, illuminating subtle distinctions in political, social and economic context which are significant in identifying receptive contexts for the adoption of modernization policies.Organized into three main themes in the modernization of the welfare state – management, governance and marketization – the contents revolve around unique empirical accounts, revealing distinctive Scandinavian characteristics of reform initiatives. The received wisdom may be a hesitant follower of the UK and the USA. But this book offers an alternative interpretation, revealing an edginess in certain Scandinavian settings, particularly in Sweden, which is a largely unrecognized.Without compromising the welfare state, it may be a bold frontrunner in the development of New Public Management.

Signal Processing for Computer Vision is a unique and thorough treatment of the signal processing aspects of filters and operators for low-level computer vision. Computer vision has progressed considerably over recent years. From methods only applicable to simple images, it has developed to deal with increasingly complex scenes, volumes and time sequences. A substantial part of this book deals with the problem of designing models that can be used for several purposes within computer vision. These partial models have some general properties of invariance generation and generality in model generation. Signal Processing for Computer Vision is the first book to give a unified treatment of representation and filtering of higher order data, such as vectors and tensors in multidimensional space. Included is a systematic organisation for the implementation of complex models in a hierarchical modular structure and novel material on adaptive filtering using tensor data representation. Signal Processing for Computer Vision is intended for final year undergraduate and graduate students as well as engineers and researchers in the field of computer vision and image processing.