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Proceedings of Academia-Industry Consortium for Data Science = AICDS 2020 /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Proceedings of Academia-Industry Consortium for Data Science/ edited by Gaurav Gupta, Lipo Wang, Anupam Yadav, Puneet Rana, Zhenyu Wang.
其他題名:
AICDS 2020 /
其他作者:
Wang, Zhenyu.
面頁冊數:
XII, 418 p. 176 illus., 122 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Machine Learning. -
電子資源:
https://doi.org/10.1007/978-981-16-6887-6
ISBN:
9789811668876
Proceedings of Academia-Industry Consortium for Data Science = AICDS 2020 /
Proceedings of Academia-Industry Consortium for Data Science
AICDS 2020 /[electronic resource] :edited by Gaurav Gupta, Lipo Wang, Anupam Yadav, Puneet Rana, Zhenyu Wang. - 1st ed. 2022. - XII, 418 p. 176 illus., 122 illus. in color.online resource. - Advances in Intelligent Systems and Computing,14112194-5365 ;. - Advances in Intelligent Systems and Computing,335.
Neural Artistic Style Transfer using Deep Neural Networks -- Choice Based One-Time Pad Approach Using Hybrid Cellular Automata -- Novel Imaging Approach for Mental Stress Detection using EEG Signals -- Classification of Fundus Images for Diabetic Retinopathy using Machine Learning: A Brief Review -- Wearable Sensor and Machine Learning Model based Fall Detection System for Safety of Elders and Movement Disorders.
This book gathers high-quality papers presented at Academia-Industry Consortium for Data Science (AICDS 2020), held in Wenzhou, China during 19 – 20 December 2020. The book presents views of academicians and also how companies are approaching these challenges organizationally. The topics covered in the book are data science and analytics, natural language processing, predictive analytics, artificial intelligence, machine learning, deep learning, big data computing, cognitive computing, data visualization, image processing, and optimization techniques.
ISBN: 9789811668876
Standard No.: 10.1007/978-981-16-6887-6doiSubjects--Topical Terms:
1137723
Machine Learning.
LC Class. No.: Q342
Dewey Class. No.: 006.3
Proceedings of Academia-Industry Consortium for Data Science = AICDS 2020 /
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