001472285 000__ 06106cam\\22006497a\4500
001472285 001__ 1472285
001472285 003__ OCoLC
001472285 005__ 20230908003404.0
001472285 006__ m\\\\\o\\d\\\\\\\\
001472285 007__ cr\un\nnnunnun
001472285 008__ 230812s2023\\\\si\\\\\\o\\\\\101\0\eng\d
001472285 020__ $$a9789819930104$$q(electronic bk.)
001472285 020__ $$a9819930103$$q(electronic bk.)
001472285 0247_ $$a10.1007/978-981-99-3010-4$$2doi
001472285 035__ $$aSP(OCoLC)1392344762
001472285 040__ $$aEBLCP$$beng$$cEBLCP$$dGW5XE
001472285 049__ $$aISEA
001472285 050_4 $$aQA75.5$$b.I58 2023eb
001472285 08204 $$a004$$223/eng/20230814
001472285 1112_ $$aInternational Conference on Innovative Computing and Communications$$n(6th :$$d2023 :$$cDelhi, India)
001472285 24510 $$aInternational Conference on Innovative Computing and Communications :$$bproceedings of ICICC 2023.$$nVolume 3 /$$cAboul Ella Hassanien, Oscar Castillo, Sameer Anand, Ajay Jaiswal, editors.
001472285 2463_ $$aICICC 2023
001472285 260__ $$aSingapore :$$bSpringer,$$c2023.
001472285 300__ $$a1 online resource (768 p.).
001472285 4901_ $$aLecture Notes in Networks and Systems ;$$vv. 537
001472285 500__ $$a5 Conclusion and Future Work
001472285 500__ $$aIncludes author index.
001472285 5050_ $$aIntro -- ICICC-2023 Steering Committee Members -- Preface -- Contents -- Editors and Contributors -- Joint Identification and Clustering Using Deep Learning Techniques -- 1 Introduction -- 1.1 Contributions -- 2 Methods -- 2.1 BlazePose -- 2.2 Keypoint RCNN -- 2.3 MMPose -- 3 Clustering of Joints -- 4 Results -- 4.1 Limitations of the Proposed Work -- 5 Conclusion and Future Scope -- References -- Comparative Analysis of Deep Learning with Different Optimization Techniques for Type 2 Diabetes Mellitus Detection Using Gene Expression Data -- 1 Introduction -- 2 Literature Survey
001472285 5058_ $$a3 Hybrid DL-Based Various Optimization Algorithms -- 3.1 Data Acquisition -- 3.2 Data Transformation by YJ -- 3.3 Selection of Features by Jaya-DOA -- 3.4 Data Augmentation -- 3.5 T2DM Detection Using Hybrid DL -- 4 Results and Discussion -- 4.1 Experimental Setup -- 4.2 Dataset Description -- 4.3 Performance Metrics -- 4.4 Comparative Methods -- 4.5 Comparative Analysis -- 4.6 Comparative Discussion -- 5 Conclusion -- References -- Differential Analysis of MOOC Models for Increasing Retention and Evaluation of the Performance of Proposed Model -- 1 Introduction -- 2 Literature Review
001472285 5058_ $$a3 Methodology -- 4 Result -- 5 Tabulation of Comparing the Performance of Concerned Research Model with Earlier Studies -- 6 Conclusion -- References -- Deep Convolutional Neural Networks Network with Transfer Learning for Image-Based Malware Analysis -- 1 Introduction -- 2 Related Works -- 3 Proposed Work Implementation -- 3.1 Convolution Neural Network -- 3.2 Transfer Learning -- 3.3 VGG-16 -- 3.4 Inception-V3 -- 3.5 ResNet-50 -- 4 Dataset -- 5 Architecture -- 6 Results and Discussion -- 7 Conclusion and Future Work -- References
001472285 5058_ $$aAnalysis of Network Failure Detection Using Machine Learning in 5G Core Networks -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 4 Experiment Results and Discussion -- 5 Conclusion -- References -- MVR Delay: Establishing Self-organizing Virtual Backhaul for Trusty, Reliable, and Timely Emergency Message Dissemination in VANET -- 1 Introduction -- 2 Related Work -- 3 Self-organizing Virtual Backhaul -- 4 Proposed Solution -- 5 Results -- 5.1 Packet Delivery Ratio by Varying the Node Density -- 5.2 Packet Delivery Ratio by Varying the Speed -- 5.3 Average Delay -- 5.4 Average Cost
001472285 5058_ $$a5.5 Fake Message Detection Accuracy -- 5.6 Stability of Virtual Backhaul -- 6 Conclusion -- References -- Machine Learning Algorithms for Prediction of Mobile Phone Prices -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 3.1 Dataset -- 3.2 Preprocessing -- 3.3 Model Building -- 4 Experimental Results and Discussion -- 5 Conclusion -- References -- Customized CNN for Traffic Sign Recognition Using Keras Pre-Trained Models -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 Approach -- 3.2 Block Diagram -- 3.3 Dataset -- 4 Experimental Setup and Results
001472285 506__ $$aAccess limited to authorized users.
001472285 520__ $$aThis book includes high-quality research papers presented at the Sixth International Conference on Innovative Computing and Communication (ICICC 2023), which is held at the Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India, on February 1718, 2023. Introducing the innovative works of scientists, professors, research scholars, students, and industrial experts in the field of computing and communication, the book promotes the transformation of fundamental research into institutional and industrialized research and the conversion of applied exploration into real-time applications.
001472285 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed August 14, 2023).
001472285 650_0 $$aComputer science$$vCongresses.
001472285 655_0 $$aElectronic books.
001472285 7001_ $$aHassanien, Aboul Ella.
001472285 7001_ $$aCastillo, Oscar,$$d1959-
001472285 7001_ $$aAnand, Sameer.
001472285 7001_ $$aJaiswal, Ajay.
001472285 77608 $$iPrint version:$$aHassanien, Aboul Ella$$tInternational Conference on Innovative Computing and Communications$$dSingapore : Springer,c2023$$z9789819930098
001472285 830_0 $$aLecture notes in networks and systems ;$$vv. 537.
001472285 852__ $$bebk
001472285 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-3010-4$$zOnline Access$$91397441.1
001472285 909CO $$ooai:library.usi.edu:1472285$$pGLOBAL_SET
001472285 980__ $$aBIB
001472285 980__ $$aEBOOK
001472285 982__ $$aEbook
001472285 983__ $$aOnline
001472285 994__ $$a92$$bISE