000			07218cam a2200781 i 4500
001			on1048047326
003			OCoLC
005			20220711203142.0
006			m o d
007			cr |||||||||||
008			180804t20182019nju ob 001 0 eng
010			_a 2018037546
040			_aDLC _beng _erda _cDLC _dOCLCF _dDG1 _dN$T _dEBLCP _dUKMGB _dUWW _dCOO _dDLC _dOCLCO _dUKAHL _dUX1 _dVT2 _dK6U
015			_aGBB956590 _2bnb
016	7		_a019327505 _2Uk
019			_a1100448615 _a1175642953 _a1181905240
020			_a9781119376989 _q(Adobe PDF)
020			_a111937698X
020			_a9781119377009 _q(ePub)
020			_a1119377005
020			_z9781119376972 (hardcover)
020			_a9781119376996 _q(electronic bk.)
020			_a1119376998 _q(electronic bk.)
020			_a1119376971
020			_a9781119376972
029	1		_aUKMGB _b019327505
029	1		_aCHVBK _b565571613
029	1		_aCHNEW _b001048762
029	1		_aAU@ _b000063820694
035			_a(OCoLC)1048047326 _z(OCoLC)1100448615 _z(OCoLC)1175642953 _z(OCoLC)1181905240
037			_a9781119377009 _bWiley
042			_apcc
050	0	0	_aQA76.9.D343
072		7	_aCOM _x021030 _2bisacsh
082	0	0	_a005.7 _223
049			_aMAIN
100	1		_aVrochidis, Stefanos, _d1975- _eauthor. _94621
245	1	0	_aBig data analytics for large-scale multimedia search / _cStefanos Vrochidis, Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece, Benoit B. Huet, EURECOM, Sophia-Antipolis, France, Edward Y. Chang, HTC Research & Healthcare San Francisco, USA, Ioannis Kompatsiaris, Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece.
263			_a1812
264		1	_aHoboken, NJ, USA : _bWiley, _c[2018]
264		4	_c©2019
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bn _2rdamedia
338			_aonline resource _bnc _2rdacarrier
504			_aIncludes bibliographical references and index.
588			_aDescription based on print version record and CIP data provided by publisher; resource not viewed.
505	0		_aCover; Title Page; Copyright; Contents; Introduction; List of Contributors; About the Companion Website; Part I Feature Extraction from Big Multimedia Data; Chapter 1 Representation Learning on Large and Small Data; 1.1 Introduction; 1.2 Representative Deep CNNs; 1.2.1 AlexNet; 1.2.1.1 ReLU Nonlinearity; 1.2.1.2 Data Augmentation; 1.2.1.3 Dropout; 1.2.2 Network in Network; 1.2.2.1 MLP Convolutional Layer; 1.2.2.2 Global Average Pooling; 1.2.3 VGG; 1.2.3.1 Very Small Convolutional Filters; 1.2.3.2 Multi-scale Training; 1.2.4 GoogLeNet; 1.2.4.1 Inception Modules; 1.2.4.2 Dimension Reduction
505	8		_a1.2.5 ResNet1.2.5.1 Residual Learning; 1.2.5.2 Identity Mapping by Shortcuts; 1.2.6 Observations and Remarks; 1.3 Transfer Representation Learning; 1.3.1 Method Specifications; 1.3.2 Experimental Results and Discussion; 1.3.2.1 Results of Transfer Representation Learning for OM; 1.3.2.2 Results of Transfer Representation Learning for Melanoma; 1.3.2.3 Qualitative Evaluation: Visualization; 1.3.3 Observations and Remarks; 1.4 Conclusions; References; Chapter 2 Concept-Based and Event-Based Video Search in Large Video Collections; 2.1 Introduction
505	8		_a2.2 Video preprocessing and Machine Learning Essentials2.2.1 Video Representation; 2.2.2 Dimensionality Reduction; 2.3 Methodology for Concept Detection and Concept-Based Video Search; 2.3.1 Related Work; 2.3.2 Cascades for Combining Different Video Representations; 2.3.2.1 Problem Definition and Search Space; 2.3.2.2 Problem Solution; 2.3.3 Multi-Task Learning for Concept Detection and Concept-Based Video Search; 2.3.4 Exploiting Label Relations; 2.3.5 Experimental Study; 2.3.5.1 Dataset and Experimental Setup; 2.3.5.2 Experimental Results; 2.3.5.3 Computational Complexity
505	8		_a2.4 Methods for Event Detection and Event-Based Video Search2.4.1 Related Work; 2.4.2 Learning from Positive Examples; 2.4.3 Learning Solely from Textual Descriptors: Zero-Example Learning; 2.4.4 Experimental Study; 2.4.4.1 Dataset and Experimental Setup; 2.4.4.2 Experimental Results: Learning from Positive Examples; 2.4.4.3 Experimental Results: Zero-Example Learning; 2.5 Conclusions; 2.6 Acknowledgments; References; Chapter 3 Big Data Multimedia Mining: Feature Extraction Facing Volume, Velocity, and Variety; 3.1 Introduction; 3.2 Scalability through Parallelization
505	8		_a3.2.1 Process Parallelization3.2.2 Data Parallelization; 3.3 Scalability through Feature Engineering; 3.3.1 Feature Reduction through Spatial Transformations; 3.3.2 Laplacian Matrix Representation; 3.3.3 Parallel latent Dirichlet allocation and bag of words; 3.4 Deep Learning-Based Feature Learning; 3.4.1 Adaptability that Conquers both Volume and Velocity; 3.4.2 Convolutional Neural Networks; 3.4.3 Recurrent Neural Networks; 3.4.4 Modular Approach to Scalability; 3.5 Benchmark Studies; 3.5.1 Dataset; 3.5.2 Spectrogram Creation; 3.5.3 CNN-Based Feature Extraction; 3.5.4 Structure of the CNNs
520			_a"A timely overview of cutting edge technologies for multimedia retrieval with a special emphasis on scalability. The amount of multimedia data available every day is enormous and is growing at an exponential rate, creating a great need for new and more efficient approaches for large scale multimedia search. This book addresses that need, covering the area of multimedia retrieval and placing a special emphasis on scalability. It reports the recent works in large scale multimedia search, including research methods and applications, and is structured so that readers with basic knowledge can grasp the core message while still allowing experts and specialists to drill further down into the analytical sections. Big Data Analytics for Large-Scale Multimedia Search covers: representation learning, concept and event-based video search in large collections; big data multimedia mining, large scale video understanding, big multimedia data fusion, large-scale social multimedia analysis, privacy and audiovisual content, data storage and management for big multimedia, large scale multimedia search, multimedia tagging using deep learning, interactive interfaces for big multimedia and medical decision support applications using large multimodal data."--Provided by publisher.
650		0	_aMultimedia data mining. _94622
650		0	_aBig data. _94174
650		7	_aCOMPUTERS _xDatabases _xData Mining. _2bisacsh _94623
650		7	_aBig data. _2fast _0(OCoLC)fst01892965 _94174
650		7	_aMultimedia data mining. _2fast _0(OCoLC)fst01982691 _94622
655		0	_aElectronic books. _93294
655		4	_aElectronic books. _93294
700	1		_aHuet, Benoit, _eauthor. _94624
700	1		_aChang, Edward Y., _eauthor. _94625
700	1		_aKompatsiaris, Yiannis, _eauthor. _94626
776	0	8	_iPrint version: _aVrochidis, Stefanos, 1975- author. _tBig data analytics for large-scale multimedia search _dHoboken, NJ, USA : Wiley, [2018] _z9781119376972 _w(DLC) 2018035613
856	4	0	_uhttps://doi.org/10.1002/9781119376996 _zWiley Online Library
942			_cEBK
994			_aC0 _bDG1
999			_c68309 _d68309