國立虎尾科技大學 |

Deep Learning in Mining of Visual Content

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Deep Learning in Mining of Visual Content/ by Akka Zemmari, Jenny Benois-Pineau.
作者:	Zemmari, Akka.
其他作者:	Benois-Pineau, Jenny.
面頁冊數:	XVII, 110 p. 46 illus., 25 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Data Mining and Knowledge Discovery. -
電子資源:	https://doi.org/10.1007/978-3-030-34376-7
ISBN:	9783030343767

Deep Learning in Mining of Visual Content
Zemmari, Akka.

Deep Learning in Mining of Visual Content[electronic resource] /by Akka Zemmari, Jenny Benois-Pineau. - 1st ed. 2020. - XVII, 110 p. 46 illus., 25 illus. in color.online resource. - SpringerBriefs in Computer Science,2191-5768. - SpringerBriefs in Computer Science,.

Introduction -- 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.

This 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.

ISBN: 9783030343767

Standard No.: 10.1007/978-3-030-34376-7doiSubjects--Topical Terms:

677765
Data Mining and Knowledge Discovery.

LC Class. No.: Q334-342

Dewey Class. No.: 006.3

Deep Learning in Mining of Visual Content
LDR:03177nam a22003975i 4500 001 1029531
003 DE-He213
005 20200701040331.0
007 cr nn 008mamaa
008 210318s2020 gw | s |||| 0|eng d
020 $a 9783030343767 $9 978-3-030-34376-7
024 7 $a 10.1007/978-3-030-34376-7 $2 doi
035 $a 978-3-030-34376-7
050 4 $a Q334-342
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
100 1 $a Zemmari, Akka. $e editor. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1300019
245 1 0 $a Deep Learning in Mining of Visual Content $h [electronic resource] / $c by Akka Zemmari, Jenny Benois-Pineau.
250 $a 1st ed. 2020.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a XVII, 110 p. 46 illus., 25 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a SpringerBriefs in Computer Science, $x 2191-5768
505 0 $a Introduction -- 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 $a This 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 2 4 $a Data Mining and Knowledge Discovery. $3 677765
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 671334
650 1 4 $a Artificial Intelligence. $3 646849
650 0 $a Data mining. $3 528622
650 0 $a Optical data processing. $3 639187
650 0 $a Artificial intelligence. $3 559380
700 1 $a Benois-Pineau, Jenny. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 891842
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030343750
776 0 8 $i Printed edition: $z 9783030343774
830 0 $a SpringerBriefs in Computer Science, $x 2191-5768 $3 1255334
856 4 0 $u https://doi.org/10.1007/978-3-030-34376-7
912 $a ZDB-2-SCS
912 $a ZDB-2-SXCS
950 $a Computer Science (SpringerNature-11645)
950 $a Computer Science (R0) (SpringerNature-43710)