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Titlebook: Intelligent Computing, Smart Communication and Network Technologies; First International Paulraj Dassan,Sethukarasi Thirumaaran,Neelakanda

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發(fā)表于 2025-3-21 17:58:09 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Intelligent Computing, Smart Communication and Network Technologies
副標(biāo)題First International
編輯Paulraj Dassan,Sethukarasi Thirumaaran,Neelakandan
視頻videohttp://file.papertrans.cn/477/476192/476192.mp4
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: Intelligent Computing, Smart Communication and Network Technologies; First International  Paulraj Dassan,Sethukarasi Thirumaaran,Neelakanda
描述.This book constitutes the refereed proceedings of the First International Conference on Intelligent Computing, Smart Communication and Network Technologies, ICICSCNT 2023, held in Chennai, India, during April 26–27, 2023...The 36 full papers included in this book were carefully reviewed and selected from 782 submissions. The main aim of ICICSCNT 2023 is to present the state-of-the-art research innovations and results in the area of intelligent systems and advanced control technologies and real-world applications in ICT research, particularly covering autonomous systems, artificial intelligence, sensing, hardware and software implementation, soft computing, optimization, intelligent control design, intelligent system integration and control applications, and other relevant research areas..
出版日期Conference proceedings 2024
關(guān)鍵詞data retrieval; information hiding; semantic information ; natural language processing; network analysis
版次1
doihttps://doi.org/10.1007/978-3-031-75957-4
isbn_softcover978-3-031-75956-7
isbn_ebook978-3-031-75957-4Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Melanoma Skin Cancer Classification Using Transfer Learning,need for early illness detection is therefore extremely important. There is a huge demand to create a system that can predict whether a person would get diseased or not, alternately, this system can prove to be of major help in hospitals and clinics.
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Detecting Fake and Genuine Facebook Users Using Gradient Boosted Trees and Interpretable Machine Lensible. The proposed system aims to objectively and fairly identify fake Facebook accounts, reducing the risk of malicious activity and improving user experience. The proposed system should use explainable AI (XAI) to increase trust in technology and ensure user security by providing transparency and interpretability in decision-making.
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發(fā)表于 2025-3-22 12:06:47 | 只看該作者
Conference proceedings 2024e, sensing, hardware and software implementation, soft computing, optimization, intelligent control design, intelligent system integration and control applications, and other relevant research areas..
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1865-0929 ntelligence, sensing, hardware and software implementation, soft computing, optimization, intelligent control design, intelligent system integration and control applications, and other relevant research areas..978-3-031-75956-7978-3-031-75957-4Series ISSN 1865-0929 Series E-ISSN 1865-0937
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發(fā)表于 2025-3-22 20:31:56 | 只看該作者
Application of Neural Nets as Computing Network in Augmenting Variables of Abrasive Machining in Poes the particle velocities and creates a whirling effect for the abrasive air mixture while cutting any material, the newly created internal threaded nozzle has been demonstrated to give greater possibilities for AJM processing. ANN was successfully used to determine the ideal machining parameters.
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Design of Metaheuristically Supervised Linear ADRC for a Magnetic Levitation System Control, with a traditional PID controller based on their dynamic response and tracking performance. The analysis showed that LADRC with cuckoo search algorithm had a better tracking performance and dynamic response.
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Heart Disease Prediction Using Machine Learning Techniques,en patterns and medical factors associated to heart disease. The training approach we used was a by different algorithms in machine learning like Random Forest, KNN, Support Vector Machine, Logistic Regression Decision Tree. The outcomes show that the developed diagnostic system can accurately identify the risk level of cardiac illnesses.
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發(fā)表于 2025-3-23 06:48:48 | 只看該作者
Real Time Sign Language Recognition Using Custom Convolutional Neural Network and YOLOv5,as chosen to create a complete pipeline from sign language to speech. The Custom CNN model’s output is input to the silero’s Text-to-Speech pre-trained model, which gives the speech version as output.
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