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Titlebook: Sustainable Advanced Computing; Select Proceedings o Sagaya Aurelia,Somashekhar S. Hiremath,Saroj Kr. B Conference proceedings 2022 The Edi

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发表于 2025-3-21 20:00:01 | 显示全部楼层 |阅读模式
书目名称Sustainable Advanced Computing
副标题Select Proceedings o
编辑Sagaya Aurelia,Somashekhar S. Hiremath,Saroj Kr. B
视频video
概述Includes select papers from the International Conference on Sustainable Advanced Computing ICSAC – 2021.Focuses on the novel research findings and innovations of various researchers.Includes a compila
丛书名称Lecture Notes in Electrical Engineering
图书封面Titlebook: Sustainable Advanced Computing; Select Proceedings o Sagaya Aurelia,Somashekhar S. Hiremath,Saroj Kr. B Conference proceedings 2022 The Edi
描述.This volume presents select proceedings of the International Conference on Sustainable Advanced Computing (ICSAC – 2021). It covers the latest research on a wide range of topics spanning theory, systems, applications, and case studies in advanced computing. Topics covered are machine intelligence, expert systems, robotics, natural language processing, cognitive science, quantum computing, deep learning, pattern recognition, human-computer interface, biometrics, graph theory, etc. The volume focuses on the novel research findings and innovations of various researchers. In addition, the book will be a promising solution for new generation-based sustainable, intelligent systems that are machine and human-centered with modern models and appropriate amalgamations of collaborative practices with a general objective of better research in all aspects of sustainable advanced computing. .
出版日期Conference proceedings 2022
关键词Machine Intelligence; Data Sciences; Cloud, Big Data and IOT; Network; Cryptography
版次1
doihttps://doi.org/10.1007/978-981-16-9012-9
isbn_softcover978-981-16-9014-3
isbn_ebook978-981-16-9012-9Series ISSN 1876-1100 Series E-ISSN 1876-1119
issn_series 1876-1100
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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Real-Time Traffic Sign Detection Under Foggy Condition helps to solve real-time problems; hence, it can be used in the study for detecting traffic signs under foggy condition. The study results revealed that the model network has accuracy of 99.8%, and the proposed algorithm detects a traffic sign under foggy conditions in 2 s per frame.
发表于 2025-3-22 08:05:25 | 显示全部楼层
Conference proceedings 2022ll be a promising solution for new generation-based sustainable, intelligent systems that are machine and human-centered with modern models and appropriate amalgamations of collaborative practices with a general objective of better research in all aspects of sustainable advanced computing. .
发表于 2025-3-22 10:35:31 | 显示全部楼层
ECG-Based Personal Identification System carried out where the mean fragment is obtained which is used in the classification stage. The classification is done using support vector machine (SVM) which gives the high accuracy of a system. The results obtained indicate that the method proposed is efficient and robust.
发表于 2025-3-22 13:32:51 | 显示全部楼层
Waste Object Segmentation for Autonomous Waste Segregationresults. We explore the possibilities of implementing the proposed technique with different kernel sizes and useful color spaces. The proposed technique yields an intersection over union (IoU) of 90.26%, mean intersection over union of 92.36%, pixel-wise precision of 94.9%, and mean pixel-wise precision of 95.72% on TACO dataset.
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A Constructive Deep Learning Applied Agent Mining for Supported Categorization Model to Forecast thes the required figure deposit for the implementation. And finally a most favorable precision is achieved, while operating the categorization model in MATLAB environment. The projected model provides an improved settlement with the contrast of established methods.
发表于 2025-3-23 01:45:18 | 显示全部楼层
High-Utility Pattern Mining Using ULB-Minern algorithms, namely UP-Hist, UFH, and ULB-Miner were used. An applied empirical evaluation shows that ULB-Miner provides better performance of the UP-Hist and UFH algorithms in terms of running time as well as memory consumption.
发表于 2025-3-23 07:29:18 | 显示全部楼层
Predictive Analytics for Real-Time Agriculture Supply Chain Management: A Novel Pilot Studya over the past decade, analytics has been gaining more significance in almost all domains with tremendous contribution to the insightful knowledge. In this paper, we present the initial walkthrough for novel predictive analytics in the field of agriculture, aimed at enhancing and strengthening the
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