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Titlebook: Cybernetics, Cognition and Machine Learning Applications; Proceedings of ICCCM Vinit Kumar Gunjan,P. N. Suganthan,Amit Kumar Conference pro

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發(fā)表于 2025-3-21 18:15:34 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Cybernetics, Cognition and Machine Learning Applications
副標題Proceedings of ICCCM
編輯Vinit Kumar Gunjan,P. N. Suganthan,Amit Kumar
視頻videohttp://file.papertrans.cn/242/241888/241888.mp4
概述Presents recent innovative research in the field of machine learning applications.Discusses the outcomes of ICCCMLA 2020, held in Goa, India.Serves as a reference resource for researchers and practiti
叢書名稱Algorithms for Intelligent Systems
圖書封面Titlebook: Cybernetics, Cognition and Machine Learning Applications; Proceedings of ICCCM Vinit Kumar Gunjan,P. N. Suganthan,Amit Kumar Conference pro
描述This book includes the original, peer reviewed research articles from the 2nd?International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA 2020), held in August, 2020 at Goa, India. It covers the latest research trends or developments in areas of data science, artificial intelligence, neural networks, cognitive science and machine learning applications, cyber physical systems and cybernetics.
出版日期Conference proceedings 2021
關(guān)鍵詞ICCCMLA 2020; Ubiquitous Intelligence and Computing; Mobile Computing; Human-Computer Interaction; Patte
版次1
doihttps://doi.org/10.1007/978-981-33-6691-6
isbn_softcover978-981-33-6693-0
isbn_ebook978-981-33-6691-6Series ISSN 2524-7565 Series E-ISSN 2524-7573
issn_series 2524-7565
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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發(fā)表于 2025-3-21 21:25:20 | 只看該作者
Simulating User Journeys with?Active Objectstabase along with the patient’s ID. The key objective of this automatic update of pulse or ECG measurements of patients is to prevent any errors caused due to their manual entry. The data of any patient can be readily accessed anytime through the EMR system.
板凳
發(fā)表于 2025-3-22 01:37:19 | 只看該作者
Fundamentals of Corrosion Kineticson v3 model gave the best training accuracy of 99.22%, while custom made CNN3 gave a promising training accuracy of 96.61%. Both models gave a similar validation accuracy of 97.89%. Sensitivity and specificity for COVID-19 were (100% and 98.5%) and (100% and 100%) for Inception v3 and CNN3, respectively.
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發(fā)表于 2025-3-22 08:10:25 | 只看該作者
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發(fā)表于 2025-3-22 13:13:28 | 只看該作者
Detecting COVID-19 Using Convolution Neural Networks,on v3 model gave the best training accuracy of 99.22%, while custom made CNN3 gave a promising training accuracy of 96.61%. Both models gave a similar validation accuracy of 97.89%. Sensitivity and specificity for COVID-19 were (100% and 98.5%) and (100% and 100%) for Inception v3 and CNN3, respectively.
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發(fā)表于 2025-3-22 20:33:19 | 只看該作者
IoT-Enabled Logistics for E-waste Management and Sustainability, create a win–win situation for both, the developed and developing countries economically and also in an environment-friendly manner. This review paper contributes to the knowledge of e-waste management and is expected to benefit the industry and society.
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發(fā)表于 2025-3-22 23:36:06 | 只看該作者
Navigation Through Proxy Measurement of Location by Surface Detection,considered surface types are captured by moving the system containing embedded IMU sensor with raspberry pi on different surfaces. Hence, a robust and portable system is developed which is capable of recognizing the type of surface on which it is navigating.
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發(fā)表于 2025-3-23 03:16:47 | 只看該作者
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發(fā)表于 2025-3-23 08:24:00 | 只看該作者
Feature Construction Through Inductive Transfer Learning in Computer Vision,nd will publish the experiment results for Inception V3, VGG16, and Resnet50 models on the ImageNet dataset by varying the image sizes for source and target datasets, for Inductive transfer Learning and various techniques or methods specially by doing the model transfer.
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