Machine learning for edge computing frameworks, patterns and best practices / edited by Amitoj Singh, Vinay Kukreja, and Taghi Javdani Gandomani.

Other author Singh, Amitoj.
Other author Kukreja, Vinay.
Other author Gandomani, Taghi Javdani, 1975-
Format Electronic
EditionFirst edition.
Publication InfoBoca Raton ; London : CRC Press, 2023.
Description1 online resource
Supplemental ContentFull text available from Taylor & Francis eBooks
Supplemental ContentFull text available from eBooks on EBSCOhost
Subjects

Contents Fog Computing And Its Security Challenges / Kamali Gupta, Deepali Gupta, Vinay Kukreja, Vipul Kaushik -- An Elucidation for Machine Learning Algorithms Used in Healthcare / Veerpal Kaur, Rajpal Kaur -- Tea Vending Machine from extracts of Natural Tea leaves and other Ingredients : IoT and Artificial Intelligence Enabled / Neha Sharma, Ram Kumar Ketti Ramachandran, Huma Naz, Rishabh Sharma -- Recent Trends in OCR Systems : A Review / Aditi Moudgil, Saravjeet Singh, Vinay Gautam -- A Novel Approach for Data Security using DNA Cryptography with Artificial Bee Colony Algorithm in Cloud Computing / Manisha Rani, Madhvi Popli, Gagandeep -- Various Techniques for Consensus Mechanism in Blockchain / Shivani Wadhwa, Gagandeep -- IoT-inspired Smart Healthcare Service for diagnosing remote patients with Diabetes / Huma Naz, Rishabh Sharma, Neha Sharma, Sachin Ahuja -- Segmentation of Deep Learning Models / Prabhjot Kaur, Anand Muni Mishra -- Alzheimer's disease Classification / M. Sethi, S. Ahuja, V. Kukreja -- Deep learning applications on Edge computing / Naresh Kumar Trivedi, Abhineet Anand, Umesh Kumar Lilhore, Kalpna Guleria -- Designing an Efficient Network-based Intrusion Detection System using Artificial Bee Colony and ADASYN oversampling approach / Manisha Rani, Gunreet Kaur, Gagandeep.
Abstract "This book divides edge intelligence into AI for edge (intelligence-enabled edge computing) and AI on edge (artificial intelligence on edge). It focuses on providing optimal solutions to the key concerns in edge computing through effective AI technologies, and it also discusses how to build AI models, i.e., model training and inference, on edge"-- Provided by publisher.
Bibliography noteIncludes bibliographical references and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Source of descriptionDescription based on print version record and CIP data provided by publisher.
Issued in other formPrint version: Machine learning for edge computing First edition. Boca Raton : CRC Press, 2022 9780367694326
Genre/formElectronic books.
LCCN 2022003447
ISBN9781000609240 (epub)
ISBN9781003143468 (ebook)
ISBN(hardback)
ISBN(paperback)

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