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001448056 001__ 1448056
001448056 003__ OCoLC
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001448056 020__ $$a9789811903861$$q(electronic bk.)
001448056 020__ $$a9811903867$$q(electronic bk.)
001448056 020__ $$z9789811903854
001448056 0247_ $$a10.1007/978-981-19-0386-1$$2doi
001448056 035__ $$aSP(OCoLC)1334888695
001448056 040__ $$aEBLCP$$beng$$epn$$cEBLCP$$dGW5XE$$dEBLCP$$dOCLCF$$dOCLCQ
001448056 049__ $$aISEA
001448056 050_4 $$aTK5101.A1$$bI48 2021eb
001448056 08204 $$a621.382$$223/eng/20220712
001448056 1112_ $$aInternational Conference on Communications, Signal Processing, and Systems$$n(10th :$$d2021 :$$cOnline)
001448056 24510 $$aCommunications, signal processing, and systems :$$bproceedings of the 10th International Conference on Communications, Signal Processing, and Systems.$$nVol. 2 /$$cQilian Liang, Wei Wang, Xin Liu, Zhenyu Na, Baoju Zhang, editors.
001448056 260__ $$aSingapore :$$bSpringer,$$c2022.
001448056 300__ $$a1 online resource (632 pages)
001448056 336__ $$atext$$btxt$$2rdacontent
001448056 337__ $$acomputer$$bc$$2rdamedia
001448056 338__ $$aonline resource$$bcr$$2rdacarrier
001448056 4901_ $$aLecture notes in electrical engineering ;$$vv. 879
001448056 500__ $$a3.2 Method of Application
001448056 500__ $$aIncludes author index.
001448056 5050_ $$aIntro -- Contents -- Online Multi-object Tracking Based on Deep Learning -- 1 Introduction -- 2 Proposed Method -- 2.1 Detection and Feature Extraction Based on Deep Learning -- 2.2 Single-Object Tracker -- 2.3 Discriminator -- 3 Experiment -- 3.1 Dataset -- 3.2 Results -- 4 Conclusion -- References -- Power Grid Industrial Control System Traffic Classification Based on Two-Dimensional Convolutional Neural Network -- 1 Introduction -- 2 Relative Works -- 3 Basic Theory -- 3.1 The Features of Power Grid ICS -- 3.2 The Traffic and Protocol of Power Grid ICS
001448056 5058_ $$a3.3 The Structure of Two-Dimensional CNN -- 4 Experiment and Result -- 4.1 Training Process and the Result -- 4.2 The Generalization Capability of Model -- 5 Conclusion -- References -- Influence of Structure Information for Cross-Domain Person Re-identification -- 1 Introduction -- 2 Proposed Method -- 2.1 Framework -- 2.2 Loss Functions -- 3 Experiments -- 3.1 Datasets -- 3.2 Experiment Settings -- 3.3 Evaluation -- 4 Conclusion -- References -- Course Quality Evaluation Based on Deep Neural Network -- 1 Introduction -- 2 Approach -- 2.1 Framework -- 2.2 Activation Function -- 3 Experiments
001448056 5058_ $$a3.1 Experiment Settings -- 3.2 Sample Data -- 3.3 Experiment Results -- 4 Conclusion -- References -- Design of Remote Indoor Environment Monitoring System Based on STM32 -- 1 Overall Design of Remote Indoor Environment Monitoring System -- 2 Sensors Introduction -- 2.1 MQ138 Formaldehyde Sensor -- 2.2 DHT11 Temperature and Humidity Sensor -- 2.3 GP2Y1010AU Dust Sensor -- 3 Remote Indoor Environment Monitor Design -- 3.1 Overall Hardware Circuit Schematic Diagram -- 3.2 Sensor and WIFI Module -- 3.3 WIFI Data Transmission Module -- 4 Results Display -- 4.1 System Function Design Drawing
001448056 5058_ $$a4.2 Test Outcome -- 5 Conclusion -- References -- Cloud Type Classification Using Multi-modal Information Based on Multi-task Learning -- 1 Introduction -- 2 Approach -- 2.1 Framework -- 2.2 Loss Function -- 2.3 Multi-task Learning -- 3 Experiments -- 3.1 Dataset -- 3.2 Experiment Settings -- 3.3 Analysis -- 4 Conclusion -- References -- A MCU-Based Wireless Motion Sensor Setup -- 1 Introduction -- 2 Algorithm -- 3 Results -- 4 Conclusion -- References -- Research on Path Planning and Tracking of Automatic Parking -- 1 Introduction -- 2 Research on Parking Path Planning and Tracking
001448056 5058_ $$a2.1 Kinematic Model of Vehicle -- 2.2 Research on Path Planning -- 2.3 Research on Path Tracking -- 3 Simulation Experiment of Path Planning and Tracking -- 3.1 Simulation Experiment of Path Planning -- 3.2 Simulation Experiment of Path Tracking -- 4 Conclusion -- References -- The Design of a Household Intelligent Medicine Box Based on the Internet of Things -- 1 Research Background and Significance -- 2 Design Scheme -- 2.1 The Mechanical Structure -- 2.2 Control System -- 2.3 Software Part -- 2.4 Component Parameters and Performance -- 3 Main Functions and Usage -- 3.1 Key Function
001448056 506__ $$aAccess limited to authorized users.
001448056 520__ $$aThis book brings together papers presented at the 2021 International Conference on Communications, Signal Processing, and Systems, which provides a venue to disseminate the latest developments and to discuss the interactions and links between these multidisciplinary fields. Spanning topics ranging from communications, signal processing and systems, this book is aimed at undergraduate and graduate students in Electrical Engineering, Computer Science and Mathematics, researchers and engineers from academia and industry as well as government employees (such as NSF, DOD and DOE).
001448056 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed July 12, 2022).
001448056 650_0 $$aTelecommunication systems$$vCongresses.
001448056 650_0 $$aSignal processing$$vCongresses.
001448056 650_0 $$aComputer networks$$vCongresses.
001448056 655_0 $$aElectronic books.
001448056 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001448056 7001_ $$aLiang, Qilian.
001448056 7001_ $$aWang, Wei.
001448056 7001_ $$aLiu, Xin$$c(Editor on Artificial Intelligence)
001448056 7001_ $$aZhang, Baoju.
001448056 77608 $$iPrint version:$$aLiang, Qilian.$$tCommunications, Signal Processing, and Systems.$$dSingapore : Springer, ©2022$$z9789811903854
001448056 830_0 $$aLecture notes in electrical engineering ;$$vv. 879.
001448056 852__ $$bebk
001448056 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-19-0386-1$$zOnline Access$$91397441.1
001448056 909CO $$ooai:library.usi.edu:1448056$$pGLOBAL_SET
001448056 980__ $$aBIB
001448056 980__ $$aEBOOK
001448056 982__ $$aEbook
001448056 983__ $$aOnline
001448056 994__ $$a92$$bISE