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. ...
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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.
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Add this copy of Sustainable IoT and Data Analytics Enabled Machine to cart. $169.08, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2024 by Springer Nature.
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New. Contains: Illustrations, black & white, Illustrations, color. Contributions to Environmental Sciences & Innovative Business Technology . VII, 175 p. 81 illus., 73 illus. in color. Intended for professional and scholarly audience.
