000 | 03874nam a22005655i 4500 | ||
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001 | 978-3-030-34376-7 | ||
003 | DE-He213 | ||
005 | 20240423125318.0 | ||
007 | cr nn 008mamaa | ||
008 | 200122s2020 sz | s |||| 0|eng d | ||
020 |
_a9783030343767 _9978-3-030-34376-7 |
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024 | 7 |
_a10.1007/978-3-030-34376-7 _2doi |
|
050 | 4 | _aQ334-342 | |
050 | 4 | _aTA347.A78 | |
072 | 7 |
_aUYQ _2bicssc |
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_aCOM004000 _2bisacsh |
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_aUYQ _2thema |
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082 | 0 | 4 |
_a006.3 _223 |
100 | 1 |
_aZemmari, Akka. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
245 | 1 | 0 |
_aDeep Learning in Mining of Visual Content _h[electronic resource] / _cby Akka Zemmari, Jenny Benois-Pineau. |
250 | _a1st ed. 2020. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2020. |
|
300 |
_aXVII, 110 p. 46 illus., 25 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aSpringerBriefs in Computer Science, _x2191-5776 |
|
505 | 0 | _aIntroduction -- Supervised Learning Problem Formulation -- Neural Networks from Scratch -- Optimization Methods -- Deep in the Wild -- Convolutional Neural Networks as Image Analysis Tool -- Dynamic Content Mining -- Case Study for Digital Cultural Content Mining -- Introducing Domain Knowledge. | |
520 | _aThis book provides the reader with the fundamental knowledge in the area of deep learning with application to visual content mining. The authors give a fresh view on Deep learning approaches both from the point of view of image understanding and supervised machine learning. It contains chapters which introduce theoretical and mathematical foundations of neural networks and related optimization methods. Then it discusses some particular very popular architectures used in the domain: convolutional neural networks and recurrent neural networks. Deep Learning is currently at the heart of most cutting edge technologies. It is in the core of the recent advances in Artificial Intelligence. Visual information in Digital form is constantly growing in volume. In such active domains as Computer Vision and Robotics visual information understanding is based on the use of deep learning. Other chapters present applications of deep learning for visual content mining. These include attention mechanisms in deep neural networks and application to digital cultural content mining. An additional application field is also discussed, and illustrates how deep learning can be of very high interest to computer-aided diagnostics of Alzheimer’s disease on multimodal imaging. This book targets advanced-level students studying computer science including computer vision, data analytics and multimedia. Researchers and professionals working in computer science, signal and image processing may also be interested in this book. | ||
650 | 0 | _aArtificial intelligence. | |
650 | 0 |
_aImage processing _xDigital techniques. |
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650 | 0 | _aComputer vision. | |
650 | 0 | _aData mining. | |
650 | 1 | 4 | _aArtificial Intelligence. |
650 | 2 | 4 | _aComputer Imaging, Vision, Pattern Recognition and Graphics. |
650 | 2 | 4 | _aData Mining and Knowledge Discovery. |
700 | 1 |
_aBenois-Pineau, Jenny. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783030343750 |
776 | 0 | 8 |
_iPrinted edition: _z9783030343774 |
830 | 0 |
_aSpringerBriefs in Computer Science, _x2191-5776 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-030-34376-7 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
942 | _cSPRINGER | ||
999 |
_c176572 _d176572 |