Big data analytics for large-scale multimedia search / (Record no. 68309)
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| fixed length control field | 07218cam a2200781 i 4500 |
| 001 - CONTROL NUMBER | |
| control field | on1048047326 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220711203142.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 180804t20182019nju ob 001 0 eng |
| 019 ## - | |
| -- | 1100448615 |
| -- | 1175642953 |
| -- | 1181905240 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781119376989 |
| -- | (Adobe PDF) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 111937698X |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781119377009 |
| -- | (ePub) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 1119377005 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781119376996 |
| -- | (electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 1119376998 |
| -- | (electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 1119376971 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781119376972 |
| 029 1# - (OCLC) | |
| OCLC library identifier | UKMGB |
| System control number | 019327505 |
| 029 1# - (OCLC) | |
| OCLC library identifier | CHVBK |
| System control number | 565571613 |
| 029 1# - (OCLC) | |
| OCLC library identifier | CHNEW |
| System control number | 001048762 |
| 029 1# - (OCLC) | |
| OCLC library identifier | AU@ |
| System control number | 000063820694 |
| 037 ## - | |
| -- | 9781119377009 |
| -- | Wiley |
| 082 00 - CLASSIFICATION NUMBER | |
| Call Number | 005.7 |
| 100 1# - AUTHOR NAME | |
| Author | Vrochidis, Stefanos, |
| 245 10 - TITLE STATEMENT | |
| Title | Big data analytics for large-scale multimedia search / |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | 1 online resource |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Cover; 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# - FORMATTED CONTENTS NOTE | |
| Remark 2 | 1.2.5 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# - FORMATTED CONTENTS NOTE | |
| Remark 2 | 2.2 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# - FORMATTED CONTENTS NOTE | |
| Remark 2 | 2.4 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# - FORMATTED CONTENTS NOTE | |
| Remark 2 | 3.2.1 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 ## - SUMMARY, ETC. | |
| Summary, etc | "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 #7 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| General subdivision | Databases |
| -- | Data Mining. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Huet, Benoit, |
| 700 1# - AUTHOR 2 | |
| Author 2 | Chang, Edward Y., |
| 700 1# - AUTHOR 2 | |
| Author 2 | Kompatsiaris, Yiannis, |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1002/9781119376996 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Hoboken, NJ, USA : |
| -- | Wiley, |
| -- | [2018] |
| 264 #4 - | |
| -- | ©2019 |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | n |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | nc |
| -- | rdacarrier |
| 588 ## - | |
| -- | Description based on print version record and CIP data provided by publisher; resource not viewed. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Multimedia data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Big data. |
| 650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | COMPUTERS |
| 650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Big data. |
| -- | (OCoLC)fst01892965 |
| 650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Multimedia data mining. |
| -- | (OCoLC)fst01982691 |
| 994 ## - | |
| -- | C0 |
| -- | DG1 |
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