
Big Visual Data Analysis by Chen Chen
This book offers an overview of traditional big visual data analysis approaches and provides state-of-the-art solutions for several scene comprehension problems, indoor/outdoor classification, outdoor scene classification, and outdoor scene layout estimation. It is illustrated with numerous natural and synthetic color images, and extensive statistical analysis is provided to help readers visualize big visual data distribution and the associated problems. Although there has been some research on big visual data analysis, little work has been published on big image data distribution analysis using the modern statistical approach described in this book. By presenting a complete methodology on big visual data analysis with three illustrative scene comprehension problems, it provides a generic framework that can be applied to other big visual data analysis tasks.-
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The Emerging Domain of Cooperating Objects
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Brain-Computer Interface Research
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Convergence of Energy, Communication and Computation in B5G Cellular Internet of Things
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Cognitive Underwater Acoustic Networking Techniques
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Optimal Impulsive Control for Cancer Therapy
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Multiband Dual-Function CMOS RFIC Filter-Switches
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Foundations of Average-Cost Nonhomogeneous Controlled Markov Chains
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Game Theoretic Approaches for Spectrum Redistribution
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An Introduction to Modelling of Power System Components
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QC-LDPC Code-Based Cryptography
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Passivity-Based Model Predictive Control for Mobile Vehicle Motion Planning
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Discrete Event Systems
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Signal Processing Approaches to Secure Physical Layer Communications in Multi-Antenna Wireless Systems
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Design and Control of Hybrid Active Power Filters
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Distributed-Order Dynamic Systems
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Compact Models and Measurement Techniques for High-Speed Interconnects
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Speech Processing and Soft Computing
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Chinese Handwriting Recognition: An Algorithmic Perspective
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Resource Management for Heterogeneous Networks in LTE Systems
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Creating New Medical Ontologies for Image Annotation
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Time-Domain Ultra-Wideband Radar, Sensor and Components
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Geometrical Methods for Power Network Analysis
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Linear Parameter-Varying Control for Engineering Applications
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Ternary Networks
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Forward Error Correction Based On Algebraic-Geometric Theory
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Analysis of TCP Performance in Data Center Networks
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Fundamentals of RCS Prediction Methodology using Parallelized Numerical Electromagnetics Code (NEC) and Finite Element Pre-processor
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Privacy-Enhancing Fog Computing and Its Applications
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Cognitive Resource Management for Heterogeneous Cellular Networks
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Internet of Things for Smart Cities
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Persuasive Recommender Systems
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Designing TSVs for 3D Integrated Circuits
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Millimeter-Wave Receiver Concepts for 77 GHz Automotive Radar in Silicon-Germanium Technology
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Introduction to Printed Electronics
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Safety Factor Profile Control in a Tokamak
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Network Reliability and Resilience
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Willemite-Based Glass Ceramic Doped by Different Percentage of Erbium Oxide and Sintered in Temperature of 500-1100C
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A Rapid Introduction to Adaptive Filtering
Chen Chen received his B.S. degree in Electrical Engineering from Beijing University of Posts and Telecommunications (BUPT) in 2010. He received his M.S. degree in Electrical Engineering from University of Southern California (USC) in 2012. At the same year, he joined the Media Communication Lab led by Professor Kuo in University of Southern California (USC), where he is pursuing her Ph.D degree in Electrical Engineering and serving as a research assistant. His research interests include image classification, image tagging and image/video processing.
Yu-Zhuo Ren received her B.S. degree in Hebei University of Technology (HUT), China, in 2011 and the M.S. degree in Electrical Engineering from University of Southern California (USC) in 2013. She is now working as a research assistant in the Media Communication Lab led by Professor Kuo. Her research interests include image understanding related problems, in the field of computer vision and machine learning.
C.-C. Jay Kuo Dr. C.-C. Jay Kuo received the B.S. degree from the National Taiwan University, Taipei, in 1980 and the M.S. and Ph.D. degrees from the Massachusetts Institute of Technology, Cambridge, in 1985 and 1987, respectively, all in Electrical Engineering. From October 1987 to December 1988, he was Computational and Applied Mathematics Research Assistant Professor in the Department of Mathematics at the University of California, Los Angeles. Since January 1989, he has been with the University of Southern California (USC).
He is presently Director of the Multimedia Communication Lab. and Professor of Electrical Engineering and Computer Science at the USC. His research interests are in the areas of multimedia data compression, communication and networking, multimedia content analysis and modeling, and information forensics and security. Dr. Kuo has guided 119 students to their Ph.D. degrees and supervised 23 postdoctoral research fellows. Currently, his research group at the USC has around 30Ph.D. students, which is one of the largest academic research groups in multimedia technologies. He is coauthor of about 220 journal papers, 850 conference papers and 12 books. He delivered over 550 invited lectures in conferences, research institutes, universities and companies.
Yu-Zhuo Ren received her B.S. degree in Hebei University of Technology (HUT), China, in 2011 and the M.S. degree in Electrical Engineering from University of Southern California (USC) in 2013. She is now working as a research assistant in the Media Communication Lab led by Professor Kuo. Her research interests include image understanding related problems, in the field of computer vision and machine learning.
C.-C. Jay Kuo Dr. C.-C. Jay Kuo received the B.S. degree from the National Taiwan University, Taipei, in 1980 and the M.S. and Ph.D. degrees from the Massachusetts Institute of Technology, Cambridge, in 1985 and 1987, respectively, all in Electrical Engineering. From October 1987 to December 1988, he was Computational and Applied Mathematics Research Assistant Professor in the Department of Mathematics at the University of California, Los Angeles. Since January 1989, he has been with the University of Southern California (USC).
He is presently Director of the Multimedia Communication Lab. and Professor of Electrical Engineering and Computer Science at the USC. His research interests are in the areas of multimedia data compression, communication and networking, multimedia content analysis and modeling, and information forensics and security. Dr. Kuo has guided 119 students to their Ph.D. degrees and supervised 23 postdoctoral research fellows. Currently, his research group at the USC has around 30Ph.D. students, which is one of the largest academic research groups in multimedia technologies. He is coauthor of about 220 journal papers, 850 conference papers and 12 books. He delivered over 550 invited lectures in conferences, research institutes, universities and companies.
| SKU | Unavailable |
| ISBN 13 | 9789811006296 |
| ISBN 10 | 9811006296 |
| Title | Big Visual Data Analysis |
| Author | Chen Chen |
| Series | Springerbriefs In Electrical And Computer Engineering |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer Verlag, Singapore |
| Year published | 2016-03-03 |
| Number of pages | 122 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |







































