Name: Iot-Enabled Convolutional Neural Networks: Techniques and Applications (en Inglés)
Price: 614769.00 COP
Availability: InStock
Author: Naved, Mohd ; Devi, V. Ajantha ; Gaur, Loveleen
ISBN: 9788770227254

portada Iot-Enabled Convolutional Neural Networks: Techniques and Applications (en Inglés)

Iot-Enabled Convolutional Neural Networks: Techniques and Applications (en Inglés)

Formato

Libro Físico

Ilustrado por

Editorial

Autor

Naved, Mohd ; Devi, V. Ajantha ; Gaur, Loveleen

Idioma

Inglés

N° páginas

362

Encuadernación

Tapa Dura

Dimensiones

23.4 x 15.6 x 2.4 cm

Peso

0.75 kg.

ISBN13

9788770227254

Categorías

Tecnologías digitales y de la información: aspectos éticos y sociales
Tecnologías inteligentes interrelacionadas
Análisis y diseño de sistemas
Inteligencia artificial

Iot-Enabled Convolutional Neural Networks: Techniques and Applications (en Inglés)

Mohd Naved (Ilustrado por) · V. Ajantha Devi (Ilustrado por) · Loveleen Gaur (Ilustrado por) · River Publishers · Tapa Dura

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Reseña del libro "Iot-Enabled Convolutional Neural Networks: Techniques and Applications (en Inglés)"

Convolutional neural networks (CNNs), a type of deep neural network that has become dominant in a variety of computer vision tasks, in recent few years has attracted interest across a variety of domains due to their high efficiency at extracting meaningful information from visual imagery. Convolutional neural networks (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 de-noising, 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 CNN's current research trends and future directions.