Sinossi
The rapid development in the area of sensor technology has been responsible for a number of societal phenomena like UGC (User Generated Content) or QS (Quantified Self). Machine learning algorithms benefit a lot from the availability of such huge volumes of digital data. For example, new technical solutions for challenges caused by the demographic change (ageing society) can be proposed in this way, especially in the context of healthcare systems in industrialised countries. The goal of this book is to present selected algorithms for Visual Scene Analysis (VSA, processing UGC) as well as for Human Data Interpretation (HDI, using data produced within the QS movement) and to expose a joint methodological basis between these two scientific directions. While VSA approaches have reached impressive robustness towards human-like interpretation of visual sensor data, HDI methods are still of limited semantic abstraction power. Using selected state-of-the-art examples, this book shows the maturity of approaches towards closing the semantic gap in both areas, VSA and HDI.
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Sensor Data Understanding (Paperback)
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Paperback. Condizione: new. Paperback. The rapid development in the area of sensor technology has been responsible for a number of societal phenomena like UGC (User Generated Content) or QS (Quantified Self). Machine learning algorithms benefit a lot from the availability of such huge volumes of digital data. For example, new technical solutions for challenges caused by the demographic change (ageing society) can be proposed in this way, especially in the context of healthcare systems in industrialised countries. The goal of this book is to present selected algorithms for Visual Scene Analysis (VSA, processing UGC) as well as for Human Data Interpretation (HDI, using data produced within the QS movement) and to expose a joint methodological basis between these two scientific directions. While VSA approaches have reached impressive robustness towards human-like interpretation of visual sensor data, HDI methods are still of limited semantic abstraction power. Using selected state-of-the-art examples, this book shows the maturity of approaches towards closing the semantic gap in both areas, VSA and HDI. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9783832546335
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Sensor Data Understanding
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Logos Verlag Berlin, 2017
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Sensor Data Understanding (Paperback)
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Logos Verlag Berlin GmbH, Berlin, 2017
ISBN 10: 3832546332
ISBN 13: 9783832546335
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Paperback. Condizione: new. Paperback. The rapid development in the area of sensor technology has been responsible for a number of societal phenomena like UGC (User Generated Content) or QS (Quantified Self). Machine learning algorithms benefit a lot from the availability of such huge volumes of digital data. For example, new technical solutions for challenges caused by the demographic change (ageing society) can be proposed in this way, especially in the context of healthcare systems in industrialised countries. The goal of this book is to present selected algorithms for Visual Scene Analysis (VSA, processing UGC) as well as for Human Data Interpretation (HDI, using data produced within the QS movement) and to expose a joint methodological basis between these two scientific directions. While VSA approaches have reached impressive robustness towards human-like interpretation of visual sensor data, HDI methods are still of limited semantic abstraction power. Using selected state-of-the-art examples, this book shows the maturity of approaches towards closing the semantic gap in both areas, VSA and HDI. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Codice articolo 9783832546335
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