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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Mohd Naved is a machine learning consultant and researcher, currently teaching in Amity International Business School (AIBS), Amity University for various degree and research programs in data science, analytics and machine learning. .
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Aggiungi al carrelloBuch. Condizione: Neu. IoT-enabled Convolutional Neural Networks | Techniques and Applications | Mohd Naved (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2023 | River Publishers | EAN 9788770227254 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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Aggiungi al carrelloBuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Convolutional neural networks (CNNs), a type of deep neural network that has become dominant in a variety of computer vision tasks, in recent years, CNNs have attracted interest across a variety of domains due to their high efficiency at extracting meaningful information from visual imagery. CNNs excel at a wide range of machine learning and deep learning tasks. As sensor-enabled internet of things (IoT) devices pervade every aspect of modern life, it is becoming increasingly critical to run CNN inference, a computationally intensive application, on resource-constrained devices.Through this edited volume, we aim to provide a structured presentation of CNN-enabled IoT applications in vision, speech, and natural language processing. This book discusses a variety of CNN techniques and applications, including but not limited to, IoT enabled CNN for speech denoising, a smart app for visually impaired people, disease detection, ECG signal analysis, weather monitoring, texture analysis, etc.Unlike other books on the market, this book covers the tools, techniques, and challenges associated with the implementation of CNN algorithms, computation time, and the complexity associated with reasoning and modelling various types of data. We have included CNNs' current research trends and future directions.