000 03241nam a22005295i 4500
001 978-981-10-5152-4
003 DE-He213
005 20200812103928.0
007 cr nn 008mamaa
008 191118s2019 si | s |||| 0|eng d
020 _a9789811051524
_9978-981-10-5152-4
024 7 _a10.1007/978-981-10-5152-4
_2doi
040 _cCUS
050 4 _aTA1630-1650
072 7 _aUYT
_2bicssc
072 7 _aCOM012000
_2bisacsh
072 7 _aUYT
_2thema
072 7 _aUYQV
_2thema
082 0 4 _a006.6
_223
082 0 4 _a006.37
_223
245 1 0 _aDeep Learning in Object Detection and Recognition
_h[electronic resource] /
_cedited by Xiaoyue Jiang, Abdenour Hadid, Yanwei Pang, Eric Granger, Xiaoyi Feng.
250 _a1st ed. 2019.
264 1 _aSingapore :
_bSpringer Singapore :
_bImprint: Springer,
_c2019.
300 _aXVI, 224 p. 113 illus., 92 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _a1. An Overview of Deep Learning -- 2. Object Detection In Deep Learning -- 3. Deep Learning in Face Recognition across Pose and Illumination -- 4. Face Anti-spoofing via Deep Local Binary Pattern -- 5. Face Anti-spoofing via Deep Local Binary Pattern -- 6. Deep Learning Architectures for Face Recognition in Video Surveillance -- 7. Deep learning for 3D data -- 8. Deep Learning based Descriptors for Object Instance Search.
520 _aThis book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in deep learning, computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks.
650 0 _aOptical data processing.
650 0 _aData mining.
650 0 _aPattern recognition.
650 1 4 _aImage Processing and Computer Vision.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I22021
650 2 4 _aData Mining and Knowledge Discovery.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I18030
650 2 4 _aPattern Recognition.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I2203X
700 1 _aJiang, Xiaoyue.
700 1 _aHadid, Abdenour.
700 1 _aPang, Yanwei.
700 1 _aGranger, Eric.
700 1 _aFeng, Xiaoyi.
856 4 0 _uhttps://doi.org/10.1007/978-981-10-5152-4
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cEBK
999 _c203836
_d203836