Proceedings of International Conference on Deep Learning, Computing and Intelligence: ICDCI 2021

ISBN-13: 9789811656514 / Angielski / Miękka / 2022 / 580 str.

Gunasekaran Manogaran; A. Shanthini; G. Vadivu

Spis treści

Classification of Blast Cells in Leukemia Using Digital Image Processing and Machine Learning.- Secured Cloud Storage System using Auto Passkey Generation.- A Novel Multi-Objective Memetic Algorithm for Mining Classifiers.- An Intelligent Road Transportation System.- Securing Data from Active Attacks in IoT: An Extensive Study.

O autorze

Dr. Gunasekaran Manogaran is currently working as Big Data Scientist at University of California, Davis, USA. He is also Adjunct Assistant Professor, Department of Computer Science and Information Engineering, Asia University, Taiwan, and Adjunct Faculty, in School of Computing, SRM Institute of Science and Technology, Kattankulathur, India. He is Visiting Researcher/Scientist at the University of La Frontera, Colombia, and the International University of La Rioja, Spain. He received his Ph.D. from the Vellore Institute of Technology University, India. He received his Bachelor of Engineering and Master of Technology from Anna University, India, and Vellore Institute of Technology University, India, respectively. He is author/co-author of more than 100 papers in conferences, book chapters, and journals, including IEEE Transactions on Industrial Informatics, IEEE Transactions on Computational Social Systems, IEEE Internet of Things, IEEE Intelligent System, IEEE Access, ACM Transactions on Multimedia Computing, Communications, and Applications.

Dr. A. Shanthini is currently working as Associate Professor in the Department of Information and Technology, SRM Institute of Science and Technology, Kattankulathur Campus, India. She received her Bachelor of Engineering, Master of Engineering and Ph.D. from Annamalai University, India. Her current research interests include IoT, machine learning, and deep learning in health care. She published two patents in the Patent Office Journal and one in Australian patent in the year 2018 and 2020, respectively. Currently, she is Principal Investigator of the project titled “Prognosis of Microaneurysm, and early diagnosis system for non-proliferative Diabetic Retinopathy using Deep Convolutional neural network” sponsored by SPARC-IITK, MHRD, Government of India, which is associated with University of California, Davis Campus, USA, and SRM IST, India, for 67 Lakhs in March 2019. She is author/co-author in 12 research articles in international journals and conferences, including SCI and Scopus indexed papers. She is Active Member of IEEE, ACM, and ISC.

Dr. G. Vadivu is working in the teaching profession for more than two decades. Currently, she is designated Professor and Head in the Department of Information Technology at SRM Institute of Science and Technology, Kattankulathur Campus, India. Her research areas include big data analytics, semantic web, data mining, and database systems. She published more than 30 research articles in a reputed journal listed in SCIE and Scopus. She has organized UGC sponsored workshop on .NET Technologies during 2006 and 2009. She received the Best Teaching Faculty Award and Certificate of Appreciation for the journal published in the year 2012. Also, she has completed Oracle Certification, Certification in Database Administration-Microsoft Technology Association, High-Impact Teaching Skills Certified by Dale Carnegie, and IBM-DB2 certification.

Blurb

This book gathers selected papers presented at the International Conference on Deep Learning, Computing and Intelligence (ICDCI 2021), organized by Department of Information Technology, SRM Institute of Science and Technology, Chennai, India, during January 7–8, 2021. The conference is sponsored by Scheme for Promotion of Academic and Research Collaboration (SPARC) in association with University of California, UC Davis and SRM Institute of Science and Technology. The book presents original research in the field of deep learning algorithms and medical imaging systems, focusing to address issues and developments in recent approaches, algorithms, mechanisms, and developments in medical imaging.