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Sustainable IoT and Data Analytics Enabled Machine Learning Techniques and Applications

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Éditeur :

Springer


Paru le : 2024-09-27

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126,59 €
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Description

This book provides a structured presentation of machine learning related to vision, speech, and natural language processing. It addresses the tools, techniques, and challenges of machine learning algorithm implementation, computation time, and the complexity of reasoning and modeling of different types of data. The book covers diverse topics such as semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, natural language processing, traffic and signaling, driverless driving, and radiology. The majority of smart applications have a need for a sustainable Internet of things (IoT) and artificial intelligence. Active research trends and future directions of machine learning under big data analytics are also discussed. Machine learning is a class of artificial neural networks that have become dominant in various computer vision tasks, attracting interest across a variety of domains as they are a type of deep neural networks efficient in extracting meaningful information from visual imagery.
Pages
175 pages
Collection
n.c
Parution
2024-09-27
Marque
Springer
EAN papier
9789819753642
EAN PDF
9789819753659
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
17
Taille du fichier
10056 Ko
Prix
126,59 €
EAN EPUB
9789819753659
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
17
Taille du fichier
29686 Ko
Prix
126,59 €

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