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Proceedings of Emerging Trends and Technologies on Intelligent Systems : ETTIS 2021 / edited by Arti Noor, Abhijit Sen, Gaurav Trivedi.
Format
Book
Language
English
Εdition
1st ed. 2022.
Published/Created
Singapore : Springer Nature Singapore : Imprint: Springer, 2022.
Description
1 online resource (361 pages)
Availability
Available Online
Springer Nature - Springer Intelligent Technologies and Robotics eBooks 2022 English International
Details
Subject(s)
Computational intelligence
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Artificial intelligence
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Computer engineering
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Computer networks
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Quantitative research
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Editor
Noor, Arti
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Sena, Abhijit̲
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Trivedi, Gaurav
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Series
Advances in Intelligent Systems and Computing, 1371
[More in this series]
Advances in Intelligent Systems and Computing, 2194-5365 ; 1371
[More in this series]
Summary note
This book presents best selected papers presented at the International Conference on Emerging Trends and Technologies on Intelligent Systems (ETTIS 2021) held from 4 – 5 March 2021 in online mode at C-DAC, Noida, India. The book includes current research works in the areas of artificial intelligence, big data, cyber-physical systems, and security in industrial/real-world settings. The book illustrates on-going research results, projects, surveying works, and industrial experiences that describe significant advances in all of the related areas.
Contents
Application Layer Ddos Attack Detection And Defense Methods
Identification and Analysis of Threat Vector for Security Evaluation of LAN
Review of Stack-Based Binary Exploitation Techniques
OntoBlogDis: A Knowledge Centric Ontology Driven Socially Aware Framework for Influential Blogger Discovery
An Ontology based Semantic Approach for First Aid Prediction in Aviation Services incorporating RBFNN over a Cloud Server
Benchmarking Analysis of CNN Architectures for Artificial Intelligence Platforms
Welding Defect Inspection using Deep learning
Image generation using GAN and their classification using SVM and CNN
VDNet: Vehicle Detection Network using Computer Vision and Deep Learning Mechanism for Intelligent Vehicle System
FCNet: Flower Classification Using Custom Made Convolution Neural Network and Transfer Learning.
Show 7 more Contents items
ISBN
981-16-3097-6
981-16-3096-8
OCLC
1273974121
Doi
10.1007/978-981-16-3097-2
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Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage.
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