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      Advanced Computing and Systems for Security

      Volume Twelve

      AvRituparna Chaki,Agostino Cortesi

      Häftad, Engelska, 2020

      Del 1136 i serien Advances in Intelligent Systems and Computing

      549 kr

      Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

      Beskrivning

      This book features extended versions of selected papers that were presented and discussed at the 7th International Doctoral Symposium on Applied Computation and Security Systems (ACSS 2020), held in Kolkata, India, on February 28–29, 2020. Organized by the Departments of Computer Science & Engineering and A. K. Choudhury School of Information Technology at the University of Calcutta, the symposium’s international partners were Ca' Foscari University of Venice, Italy, and Bialystok University of Technology, Poland. The topics covered include biometrics, image processing, pattern recognition, algorithms, cloud computing, wireless sensor networks, and security systems, reflecting the various symposium sessions.

      Produktinformation

      • Utgivningsdatum:2020-02-02
      • Mått:155 x 235 x 9 mm
      • Vikt:274 g
      • Format:Häftad
      • Språk:Engelska
      • Serie:Advances in Intelligent Systems and Computing
      • Antal sidor:142
      • Förlag:Springer Verlag, Singapore
      • ISBN:9789811529290

      Utforska kategorier

      • Övrig teknik och tillämpad vetenskap inom Naturvetenskap och teknik
      • Systemvetenskap och AI inom Data och IT
      • Artificiell intelligens inom Data och IT

      Mer om författaren

      Rituparna Chaki is a Professor of Information Technology at the University of Calcutta, India. She received her Ph.D. from Jadavpur University, India, in 2003 and has been with the University of Calcutta since 2013. Her research interests include optical networks, sensor networks, mobile ad hoc networks, the Internet of Things, data mining, etc.Agostino Cortesi, Ph.D., is a Full Professor of Computer Science at Ca' Foscari University, Venice, Italy. He has previously served as Dean of Computer Science studies, as Department Chair, and as Vice-Rector for quality assessment and institutional affairs. His research interests include programming languages theory, software engineering, and static analysis techniques, with particular emphasis on security applications. Khalid Saeed is a Full Professor at the Faculty of Computer Science, Bialystok University of Technology, Poland. His research interests include biometrics, image analysisand processing, and computer information systems. Nabendu Chaki is a Professor at the Department of Computer Science & Engineering, University of Calcutta, India.Dr. Nabendu Chaki completed his initial Physics studies at the legendary Presidency College in Kolkata, followed by Computer Science & Engineering studies at the University of Calcutta. He received his Ph.D. from Jadavpur University, India, in 2000. He holds six international patents, including four U.S. patents with his students. Prof. Chaki has been highly active in developing international standards for software engineering and cloud computing as a member of the Global Directory (GD) for ISO-IEC.

      Innehållsförteckning

      • Automatic caption generation of retinal diseases with self trained RNN merge model.- Dimensionality reduction of hyperspectral images: A data driven approach for band selection.- Comment-Mine -- A Semantic Search Approach to Program Comprehension from Code Comments.- Biomarker Gene Identification using a Quantum Inspired Clustering Approach.- Shot Classification and Replay Detection in Broadcast Soccer Video.- A Novel Automated Blood Cell Counting Method Based on Deconvolution and Convolution and Its Application to Neural Networks.- A citizen centred sentiment analysis towards India's critically endangered Avian and Mammalian species.- Methodology for Generating Synthetic Time-dependant Probabilistic Speed Profiles.- A Multi-scale Patch-based Deep learning system for Polyp Segmentation.- Object detection in rainy condition from video using YOLO based deep learning model.- Visualisation of the evacuation process including people with heart diseases.
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