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Big Data Analysis and Deep Learning Applications: Proceedings of the First International Conference on Big Data Analysis and Deep Learning de Thi Thi Zin

Big Data Analysis and Deep Learning Applications: Proceedings of the First International Conference on Big Data Analysis and Deep Learning: Advances in Intelligent Systems and Computing, cartea 744

Editat de Thi Thi Zin, Jerry Chun-Wei Lin
en Limba Engleză Paperback – 7 iun 2018
This book presents a compilation of selected papers from the first International Conference on Big Data Analysis and Deep Learning Applications (ICBDL 2018), and focuses on novel techniques in the fields of big data analysis, machine learning, system monitoring, image processing, conventional neural networks, communication, industrial information, and their applications. Readers will find insights to help them realize more efficient algorithms and systems used in real-life applications and contexts, making the book an essential reference guide for academic researchers, professionals, software engineers in the industry, and regulators of aviation authorities. 
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Specificații

ISBN-13: 9789811308680
ISBN-10: 9811308683
Pagini: 371
Ilustrații: XIV, 386 p. 190 illus.
Dimensiuni: 155 x 235 x 33 mm
Greutate: 0.56 kg
Ediția:1st ed. 2019
Editura: Springer Nature Singapore
Colecția Springer
Seria Advances in Intelligent Systems and Computing

Locul publicării:Singapore, Singapore

Cuprins

Big data analysis.- Machine learning and applications.- Monitoring system by using image processing.- Conventional neural networks and its applications.- Information and communication.- Industrial information systems and applications.

Notă biografică

Thi Thi Zin received her Ph.D. degree in the field of Image Processing in 2007 from Osaka City University, Japan. From 2007 to 2009, she was awarded a postdoctoral research fellowship of Japan Society for the Promotion of Science (JSPS). After the JSPS, she worked as a specially appointed researcher and specially appointed assistant professor at the University of Tokyo and Osaka City University until 2013. In 2016, she became a professor at the Faculty of Engineering, University of Miyazaki, Japan. Her research interests include human behavior understanding, intelligent transportation systems, cow behavior analysis, health care monitoring systems, and image recognition. She is a member of IEEE.
Jerry Chun-Wei Lin is currently an associate professor at the School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), China. He has published more than 200 research papers (90 SCI papers) and international conferences. His research interests include data mining, soft computing, artificial intelligence, social computing, multimedia and image processing, and privacy-preserving and security technologies. He is the Editor-in-Chief of the journal Data Science and Pattern Recognition (DSPR), associate editor of Journal of Network Intelligence, associate editor of Journal of Internet Technology (JIT), and the editorial board member of Intelligent Data Analysis (IDA). He is also the leader of SPMF project, which provides more than 130 data mining algorithms and has been widely cited in many different applications.

Textul de pe ultima copertă

This book presents a compilation of selected papers from the first International Conference on Big Data Analysis and Deep Learning Applications (ICBDL 2018), and focuses on novel techniques in the fields of big data analysis, machine learning, system monitoring, image processing, conventional neural networks, communication, industrial information, and their applications. Readers will find insights to help them realize more efficient algorithms and systems used in real-life applications and contexts, making the book an essential reference guide for academic researchers, professionals, software engineers in the industry, and regulators of aviation authorities. 

Caracteristici

Gathers selected papers presenting cutting-edge findings in the fields of big data analysis, machine learning, and system monitoring Brings together new techniques and systems proposed by prominent researchers, scholars, and practitioners Provides applicable big data methods and deep learning theories, and discusses their use in real-world situations