Machine Learning, Image Processing, Network Security and Data Sciences: Select Proceedings of 3rd International Conference on MIND 2021

ISBN-13: 9789811958670 / Angielski / Twarda / 2023 / 913 str.

Rajesh Doriya; Badal Soni; Anupam Shukla

Opis

This book constitutes the refereed proceedings of the Third International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2021. The papers are organized according to the following topical sections: data science and big data; image processing and computer vision; machine learning and computational intelligence; network and cybersecurity. This book aims to develop an understanding of image processing, networks, and data modeling by using various machine learning algorithms for a wide range of real-world applications. In addition to providing basic principles of data processing, this book teaches standard models and algorithms for data and image analysis. 

Spis treści

A Methodological review of Time Series Forecasting with Deep Learning Model : A Case study on Electricity Load and Price Prediction.- A Robust Secure Access Entrance Method Based on Multi Model Biometric Credentials Iris and Finger Print.- Prostate Cancer Grading using Multistage Deep

Neural Networks.

O autorze

Rajesh Doriya received his B.E. from MITS Gwalior, M.Tech. from IIIT Allahabad, and Ph.D. from IIIT Allahabad, India. He has got teaching experience of over 10 years, and presently, he is working as an Assistant Professor in the Department of Information Technology, NIT Raipur. He is associated with research projects at the Institute for System Studies & Analyses (ISSA) lab of DRDO, New Delhi, India, and the Division of Remote Handling & Robotics (DRHR) lab of BARC Mumbai, India. He has authored over 50 research papers published in international Journals and Conferences. His research interests include distributed computing, cloud computing, artificial intelligence, robotics, soft computing techniques, network security, etc.

Badal Soni is an Assistant Professor in the Department of Computer Engineering, National Institute of Technology (NIT) Silchar, India. He completed his B. Tech. from Rajiv Gandhi Technical University (formerly RGPV) Bhopal, India, and M. Tech. from Indian Institute of Information Technology (IIITDM) Jabalpur, India. He received his Ph.D. from NIT Silchar, India. He has teaching and research experience of over seven years in computer science and information technology with a particular interest in computer graphics, image processing, speech, and language processing. He has published over 50 papers in international journals and conference proceedings. He is a Senior Member of IEEE and a professional member of various bodies like IEEE, ACM, IAENG, and IACSIT.

Anupam Shukla is working as Director at the Indian Institute of Information Technology, Pune. Before this, he was a founding Dean of Sponsored Research and Consultancy, Professor in the Department of Information and Communication Technology (ICT) at ABV-Indian Institute of Information Technology and Management (ABV-IIITM), Gwalior, and a visiting professor at Florida International University, USA, and Indian Institute of Management (IIM), Rohtak. He has 32 years of teaching and research experience. He is globally renowned for his research on artificial intelligence, which has won him several academic accolades and resulted in collaborations with academicians worldwide. To his credit, he has five patents, five books, and 190 peer-reviewed publications. He is the mentor of 17 doctorates and 146 postgraduate theses.

Xiao-Zhi Gao received his B.Sc. and M.Sc. degrees from the Harbin Institute of Technology, China, in 1993 and 1996, respectively. He obtained his D.Sc. (Tech.) degree from the Helsinki University of Technology (now Aalto University), Finland, in 1999. He has been working as a professor at the University of Eastern, Finland, since 2018. He has published over 450 technical papers in refereed journals and international conferences. His research interests are nature-inspired computing methods with their applications in optimization, data mining, machine learning, control, signal processing, and industrial electronics.