Intelligent Computing and Applications (eBook, PDF)
Proceedings of ICDIC 2020
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Intelligent Computing and Applications (eBook, PDF)
Proceedings of ICDIC 2020
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This book presents novel work of academicians, researchers, industry professionals, practitioners, and budding engineers to disseminate the most recent innovations, trends, and concerns along with the present-day challenges and the solving approaches for implementation in the domains of data science, intelligent computing, and computer networks and security. It is a collection of selected high-quality research papers from the International Conference on Data Science, Intelligent Computing and Cyber Security (ICDIC 2020) organized by Sree Vidyanikethan Engineering College, Tirupati, India,…mehr
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This book presents novel work of academicians, researchers, industry professionals, practitioners, and budding engineers to disseminate the most recent innovations, trends, and concerns along with the present-day challenges and the solving approaches for implementation in the domains of data science, intelligent computing, and computer networks and security. It is a collection of selected high-quality research papers from the International Conference on Data Science, Intelligent Computing and Cyber Security (ICDIC 2020) organized by Sree Vidyanikethan Engineering College, Tirupati, India, during 27–29 February 2020. It discusses the latest challenges and solutions in the field of data innovation, data management, data analysis, data security, and intelligent methods and applications.
Produktdetails
- Produktdetails
- Verlag: Springer Nature Singapore
- Erscheinungstermin: 13. November 2022
- Englisch
- ISBN-13: 9789811941627
- Artikelnr.: 66408319
- Verlag: Springer Nature Singapore
- Erscheinungstermin: 13. November 2022
- Englisch
- ISBN-13: 9789811941627
- Artikelnr.: 66408319
Dr. B .Narendra Kumar Rao is currently Professor and Head of the Department of Computer Science and Engineering at Sree Vidyanikethan Engineering College, Tirupati, Andhra Pradesh, India. He published and authored in reputed journals and books to his credit. He is part of Intelligent Computing Research Centre at Sree Vidyanikethan Engineering College, Tirupati. His areas of research include Software Engineering and Deep Learning.
Professor R. Balasubramanian is currently with the Department of Computer Science and Engineering, Indian Institute of Technology, Roorkee, India. His areas of interest include computer vision, image processing, machine learning and other allied areas. Being an active researcher he is part of several reputed research labs such as SeSaMe Research centre, National University of Singapore, SINGAPORE, School of Computer Sciences, Universiti Sains Malaysia, Pulau Pinag, Malaysia, Faculty of Computing and Informatics, Multimedia University, Cyberjaya Campus, Malaysia, and Department of Computer Science, University at Albany-State University of New York (SUNY), NY, USA. So far, he has published more than 130 international journals, 125 conference proceedings, 7 book chapters and a technical report. He is the recipient of BOYSCAST fellowship (awarded by DST, India). He is also the recipient of "Outstanding Teacher Award 2010" awarded by IIT Roorkee.
Professor Shiuh-Jeng WANG is currently with the Dept. of Information Management at Central Police University, Taoyuan, Taiwan, where he directs the Information Cryptology and Construction Laboratory (ICCL). He was a recipient of the 5th Acer Long-Tung Master Thesis Award and the 10th Acer Long-Tung Ph.D. Dissertation Award in 1991 and 1996, respectively. He served the editor-in-chief of the journal of Communications of the CCISA in Taiwan from 2000 to 2006. He authored eight books: Information Security, Cryptography and Network Security, State of the Art on Internet Security and Digital Forensics, Eyes of Privacy–Information Security and Computer Forensics, Information Multimedia Security, Computer Forensics and Digital Evidence, Computer Forensics and Security Systems, and Computer and Network Security in Practice, published in 2003, 2004, 2006, 2007, and 2009, respectively.
Associate Professor Richi Nayak is with the School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane, Australia. She is Head of the Data Science Discipline in EECS. She is an internationally recognised expert in data mining, text mining, and web intelligence. She has combined knowledge in these areas very successfully with diverse disciplines such as Social Science, Science, and Engineering for technology transfer to real-world problems to change their practices and methodologies. Her particular research interests aremachine learning, and in recent years, she has concentrated her work on text mining, personalization, automation, and social network analysis. She has published high-quality conference and journal articles and highly cited in her research field. She has received a number of awards and nominations for teaching, research, and service activities.
Professor R. Balasubramanian is currently with the Department of Computer Science and Engineering, Indian Institute of Technology, Roorkee, India. His areas of interest include computer vision, image processing, machine learning and other allied areas. Being an active researcher he is part of several reputed research labs such as SeSaMe Research centre, National University of Singapore, SINGAPORE, School of Computer Sciences, Universiti Sains Malaysia, Pulau Pinag, Malaysia, Faculty of Computing and Informatics, Multimedia University, Cyberjaya Campus, Malaysia, and Department of Computer Science, University at Albany-State University of New York (SUNY), NY, USA. So far, he has published more than 130 international journals, 125 conference proceedings, 7 book chapters and a technical report. He is the recipient of BOYSCAST fellowship (awarded by DST, India). He is also the recipient of "Outstanding Teacher Award 2010" awarded by IIT Roorkee.
Professor Shiuh-Jeng WANG is currently with the Dept. of Information Management at Central Police University, Taoyuan, Taiwan, where he directs the Information Cryptology and Construction Laboratory (ICCL). He was a recipient of the 5th Acer Long-Tung Master Thesis Award and the 10th Acer Long-Tung Ph.D. Dissertation Award in 1991 and 1996, respectively. He served the editor-in-chief of the journal of Communications of the CCISA in Taiwan from 2000 to 2006. He authored eight books: Information Security, Cryptography and Network Security, State of the Art on Internet Security and Digital Forensics, Eyes of Privacy–Information Security and Computer Forensics, Information Multimedia Security, Computer Forensics and Digital Evidence, Computer Forensics and Security Systems, and Computer and Network Security in Practice, published in 2003, 2004, 2006, 2007, and 2009, respectively.
Associate Professor Richi Nayak is with the School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane, Australia. She is Head of the Data Science Discipline in EECS. She is an internationally recognised expert in data mining, text mining, and web intelligence. She has combined knowledge in these areas very successfully with diverse disciplines such as Social Science, Science, and Engineering for technology transfer to real-world problems to change their practices and methodologies. Her particular research interests aremachine learning, and in recent years, she has concentrated her work on text mining, personalization, automation, and social network analysis. She has published high-quality conference and journal articles and highly cited in her research field. She has received a number of awards and nominations for teaching, research, and service activities.
Prediction of Depression Related Posts in Instagram Social Media Platform.- Classification of Credit Card Frauds Using Autoencoded Feature.- BIVFN: Blockchain-enabled Intelligent Vehicular Fog Networks.- Deep Learning Approach for Pedestrian Detection, Tracking, Suspicious Activity Recognition in Academic Environment.- Data-Driven Approach to Deflate Consumption in Delay Tolerant Networks.- Code-level Self-adaptive Approach for Building Reusable Software Components.- Design of a Deep Network Model for Weed Classification.- E-Voting System using U-Net Architecture with Blockchain Technology.- Multilayered Architecture to Monitor and Control the Energy Management in Smart Cities.- Bio-inspired Firefly Algorithm for Polygonal Approximation on Various Shapes.- An Efficient IoT Security Solution using Deep Learning Mechanisms.
Prediction of Depression Related Posts in Instagram Social Media Platform.- Classification of Credit Card Frauds Using Autoencoded Feature.- BIVFN: Blockchain-enabled Intelligent Vehicular Fog Networks.- Deep Learning Approach for Pedestrian Detection, Tracking, Suspicious Activity Recognition in Academic Environment.- Data-Driven Approach to Deflate Consumption in Delay Tolerant Networks.- Code-level Self-adaptive Approach for Building Reusable Software Components.- Design of a Deep Network Model for Weed Classification.- E-Voting System using U-Net Architecture with Blockchain Technology.- Multilayered Architecture to Monitor and Control the Energy Management in Smart Cities.- Bio-inspired Firefly Algorithm for Polygonal Approximation on Various Shapes.- An Efficient IoT Security Solution using Deep Learning Mechanisms.
Prediction of Depression Related Posts in Instagram Social Media Platform.- Classification of Credit Card Frauds Using Autoencoded Feature.- BIVFN: Blockchain-enabled Intelligent Vehicular Fog Networks.- Deep Learning Approach for Pedestrian Detection, Tracking, Suspicious Activity Recognition in Academic Environment.- Data-Driven Approach to Deflate Consumption in Delay Tolerant Networks.- Code-level Self-adaptive Approach for Building Reusable Software Components.- Design of a Deep Network Model for Weed Classification.- E-Voting System using U-Net Architecture with Blockchain Technology.- Multilayered Architecture to Monitor and Control the Energy Management in Smart Cities.- Bio-inspired Firefly Algorithm for Polygonal Approximation on Various Shapes.- An Efficient IoT Security Solution using Deep Learning Mechanisms.
Prediction of Depression Related Posts in Instagram Social Media Platform.- Classification of Credit Card Frauds Using Autoencoded Feature.- BIVFN: Blockchain-enabled Intelligent Vehicular Fog Networks.- Deep Learning Approach for Pedestrian Detection, Tracking, Suspicious Activity Recognition in Academic Environment.- Data-Driven Approach to Deflate Consumption in Delay Tolerant Networks.- Code-level Self-adaptive Approach for Building Reusable Software Components.- Design of a Deep Network Model for Weed Classification.- E-Voting System using U-Net Architecture with Blockchain Technology.- Multilayered Architecture to Monitor and Control the Energy Management in Smart Cities.- Bio-inspired Firefly Algorithm for Polygonal Approximation on Various Shapes.- An Efficient IoT Security Solution using Deep Learning Mechanisms.