001451991 000__ 04104cam\a2200685\i\4500
001451991 001__ 1451991
001451991 003__ OCoLC
001451991 005__ 20230310003335.0
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001451991 019__ $$a1354631113$$a1355220216
001451991 020__ $$a9783031207136$$q(electronic bk.)
001451991 020__ $$a3031207130$$q(electronic bk.)
001451991 020__ $$z9783031207129
001451991 020__ $$z3031207122
001451991 0247_ $$a10.1007/978-3-031-20713-6$$2doi
001451991 035__ $$aSP(OCoLC)1356305717
001451991 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX$$dEBLCP$$dOCLCQ$$dBRX$$dUKAHL
001451991 049__ $$aISEA
001451991 050_4 $$aQ337.5
001451991 08204 $$a006.4$$223/eng/20221228
001451991 1112_ $$aInternational Symposium on Visual Computing$$n(17th :$$d2022 :$$cSan Diego, Calif.).
001451991 24510 $$aAdvances in visual computing :$$b17th international symposium, ISVC 2022, San Diego, CA, USA, October 3-5, 2022, proceedings.$$nPart I /$$cGeorge Bebis, Bo Li, Angela Yao, Yang Liu, Ye Duan, Manfred Lau, Rajiv Khadka, Ana Crisan, Remco Chang (eds.).
001451991 24630 $$aISVC 2022
001451991 264_1 $$aCham :$$bSpringer,$$c[2022]
001451991 264_4 $$c©2022
001451991 300__ $$a1 online resource (xxx, 471 pages) :$$billustrations (chiefly color).
001451991 336__ $$atext$$btxt$$2rdacontent
001451991 337__ $$acomputer$$bc$$2rdamedia
001451991 338__ $$aonline resource$$bcr$$2rdacarrier
001451991 4901_ $$aLecture notes in computer science,$$x1611-3349 ;$$v13598
001451991 500__ $$aInternational conference proceedings.
001451991 500__ $$aIncludes author index.
001451991 504__ $$aReferences -- Deep Learning Based Shrimp Classification -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Acquisition -- 3.2 Preprocessing -- 3.3 Classification -- 4 Experimental Results -- 5 Conclusions -- References -- Gait Emotion Recognition Using a Bi-modal Deep Neural Network -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 4 Experimental Results -- 5 Conclusion and Future Work -- References -- Attacking Frequency Information with Enhanced Adversarial Networks to Generate Adversarial Samples -- 1 Introduction -- 2 Related Work -- 2.1 Adversarial Samples
001451991 5050_ $$aDeep Learning I -- Visualization -- Object Detection and Recognition -- Deep Learning II -- Video Analysis and Event Recognition -- Computer Graphics -- ST: Biomedical Imaging Techniques for Cancer Detection, Diagnosis and Management.
001451991 506__ $$aAccess limited to authorized users.
001451991 520__ $$aThis two-volume set of LNCS 13598 and 13599 constitutes the refereed proceedings of the 17th International Symposium on Visual Computing, ISVC 2022, which was held in October 2022. The 61 papers presented in these volumes were carefully reviewed and selected from 110 submissions. They are organized in the following topical sections: Part I: deep learning I; visualization; object detection and recognition; deep learning II; video analysis and event recognition; computer graphics; ST: biomedical imaging techniques for cancer detection, diagnosis and management. Part II: ST: neuro-inspired artificia intelligence; applications; segmentation and tracking; virtual reality; poster.
001451991 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed December 28, 2022).
001451991 650_0 $$aComputer graphics$$vCongresses.
001451991 650_0 $$aComputer vision$$vCongresses.
001451991 655_0 $$aElectronic books.
001451991 655_7 $$aConference papers and proceedings.$$2lcgft
001451991 7001_ $$aBebis, George,$$eeditor.
001451991 7001_ $$aLi, Bo,$$eeditor.
001451991 7001_ $$aYao, Angela,$$eeditor.
001451991 7001_ $$aLiu, Yang,$$eeditor.
001451991 7001_ $$aDuan, Ye,$$eeditor.
001451991 7001_ $$aLau, Manfred,$$eeditor.
001451991 7001_ $$aKhadka, Rajiv,$$eeditor.
001451991 7001_ $$aCrisan, Ana,$$eeditor.
001451991 7001_ $$aChang, Remco,$$eeditor.
001451991 77608 $$iPrint version: $$z3031207122$$z9783031207129$$w(OCoLC)1346535413
001451991 830_0 $$aLecture notes in computer science ;$$v13598.$$x1611-3349
001451991 852__ $$bebk
001451991 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-20713-6$$zOnline Access$$91397441.1
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001451991 980__ $$aBIB
001451991 980__ $$aEBOOK
001451991 982__ $$aEbook
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