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Machine Learning and Information Processing

Proceedings of ICMLIP 2020

  • Conference proceedings
  • © 2021

Overview

Editors:
  1. Debabala Swain

    1. Department of Computer Science, Rama Devi Women’s University, Bhubaneswar, India

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  2. Prasant Kumar Pattnaik

    1. School of Computer Engineering, Kalinga Institute of Industrial Technology Deemed University, Bhubaneswar, India

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  3. Tushar Athawale

    1. Oak Ridge National Laboratory, Tennessee, USA

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  • Presents recent research in the field of machine learning and information processing
  • Discusses the outcomes of ICMLIP 2020, held in Hyderabad, India
  • Serves as a reference resource for researchers and practitioners in academia and industry

Part of the book series: Advances in Intelligent Systems and Computing (AISC, volume 1311)

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Table of contents (55 papers)

  1. Front Matter

    Pages i-xvii
    Download chapter PDF

  2. Smart Queue Shopping Using RFID System

    • Debabrata Swain, Himanshu Pandey, Bhargav Pawar, Nishant Bhat, Abhijit Gawai
    Pages 1-11

  3. Prediction and Classification of Biased and Fake News Using NLP and Machine Learning Models

    • Premanand Ghadekar, Mohit Tilokchandani, Anuj Jevrani, Sanjana Dumpala, Sanchit Dass, Nikhil Shinde
    Pages 13-20

  4. Smart Leaf Disease Detection Using Image Processing

    • Amit Thakur, Nachiket K. Kulkarni, Tanay Rajwal, Vivek Deshpande
    Pages 21-32

  5. Unsupervised Image Generation and Manipulation Using Deep Convolutional Adversarial Networks

    • Premanand Ghadekar, Shaunak Joshi, Yogini Kokate, Harshada Kude
    Pages 33-43

  6. A Suicide Prediction System Based on Twitter Tweets Using Sentiment Analysis and Machine Learning

    • Debabrata Swain, Aneesh Khandelwal, Chaitanya Joshi, Abhijeet Gawas, Prateek Roy, Vishwesh Zad
    Pages 45-58

  7. Video Categorization Based on Sentiment Analysis of YouTube Comments

    • Debabrata Swain, Monika Verma, Sayali Phadke, Shraddha Mantri, Anirudha Kulkarni
    Pages 59-67

  8. Credit Score Prediction Using Machine Learning

    • Debabrata Swain, Raunak Agrawal, Ayush Chandak, Vedant Lapshetwar, Naman Chandak, Ashish Vaswani
    Pages 69-81

  9. Stock Market Prediction Using Long Short-Term Memory Model

    • Debabrata Swain, Vijeta, Soham Manjare, Sachin Kulawade, Tanuj Sharma
    Pages 83-90

  10. Efficient Management of Web Personalization Through Entropy and Similarity Analysis

    • Sujata H. Asabe, Ashish Suryawanshi, Vinit Joshi, Deepesh Abhichandan, Gourav Jain
    Pages 91-102

  11. Artistic Media Stylization and Identification Using Convolution Neural Networks

    • Premanand Ghadekar, Shaunak Joshi, Yogini Kokate, Harshada Kude
    Pages 103-115

  12. Performance Analysis of Different Models for Twitter Sentiment

    • Deepali J. Joshi, Tasmiya Kankurti, Akshada Padalkar, Rutvik Deshmukh, Shailesh Kadam, Tanay Vartak
    Pages 117-125

  13. Electricity Forecasting Using Machine Learning: A Review

    • Shital Pawar, Prajakta Mole, Shweta Phadtare, Dhanashri Aghor, Pranali Vadtile
    Pages 127-134

  14. End to End Learning Human Pose Detection Using Convolutional Neural Networks

    • Nilesh D. Navghare, L. Mary Gladence
    Pages 135-142

  15. Conference Paper Acceptance Prediction: Using Machine Learning

    • Deepali J. Joshi, Ajinkya Kulkarni, Riya Pande, Ishwari Kulkarni, Siddharth Patil, Nikhil Saini
    Pages 143-152

  16. Object Identification and Tracking Using YOLO Model: A CNN-Based Approach

    • Shweta Singh, Ajay Suri, J. N. Singh, Muskan Singh, Nikita, Dileep Kumar Yadav
    Pages 153-160

  17. Real-Time Hands-Free Mouse Control for Disabled

    • Premanand Ghadekar, Pragya Korpal, Pooja Chendake, Raksha Bansal, Apurva Pawar, Siddhi Bhor
    Pages 161-170

  18. Accounting Fraud Detection Using K-Means Clustering Technique

    • Giridhari Sahoo, Sony Snigdha Sahoo
    Pages 171-180

  19. Transforming the Lives of Socially Dependent to Self-dependent Using IoT

    • Debabala Swain, Sony Snigdha Sahoo
    Pages 181-188

  20. Enforcement an Evidence and Quality of Query Services in the Cost-Effective Cloud

    • G. Vijendar Reddy, Shaik Arshia Zainab, Sathish Vuyyala, Nagubandi Naga Lakshmi
    Pages 189-196
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Keywords

About this book

This book includes selected papers from the 2nd International Conference on Machine Learning and Information Processing (ICMLIP 2020), held at Vardhaman College of Engineering, Jawaharlal Nehru Technological University (JNTU), Hyderabad, India, from November 28 to 29, 2020. It presents the latest developments and technical solutions in the areas of advanced computing and data sciences, covering machine learning, artificial intelligence, human–computer interaction, IoT, deep learning, image processing and pattern recognition, and signal and speech processing.

Editors and Affiliations

  • Department of Computer Science, Rama Devi Women’s University, Bhubaneswar, India

    Debabala Swain

  • School of Computer Engineering, Kalinga Institute of Industrial Technology Deemed University, Bhubaneswar, India

    Prasant Kumar Pattnaik

  • Oak Ridge National Laboratory, Tennessee, USA

    Tushar Athawale

About the editors

Debabala Swain is working as Associate Professor in the Department of Computer Science, Rama Devi Women’s University, Bhubaneswar, India. She has more than a decade of teaching and research experience. Dr. Swain has published number of research papers in peer-reviewed international journals, conferences, and book chapters. She has edited books of Springer, IEEE. Her area of research interest includes high-performance computing, information security, machine learning, and IoT.


Prasant Kumar Pattnaik, Ph.D. (Computer Science), Fellow of IETE, Senior Member of IEEE, is Professor at the School of Computer Engineering, KIIT Deemed University, Bhubaneswar. He has more than a decade of teaching and research experience. Dr. Pattnaik has published numbers of research papers in peer-reviewed international journals and conferences. He also published many edited book volumes in Springer and IGI Global Publication. His areas of interest include mobile computing, cloud computing, cyber security, intelligent systems, and brain–computer interface. He is one of the Associate Editors of Journal of Intelligent & Fuzzy Systems, IOS Press, and Intelligent Systems Book Series Editor of CRC Press, Taylor Francis Group.


Tushar Athawale is currently working as Computer Scientist at Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA. He is in the domain of scientific visualization for analysis of large-scale data using tools, such as VisIt and ParaView and software development for multi-threaded visualization toolkit (VTK-m). He was Postdoctoral Fellow at the University of Utah’s Scientific Computing & Imaging (SCI) Institute with Prof. Chris R. Johnson as his advisor since October 2016. He received Ph.D. in Computer Science from the University of Florida in May 2015, and he worked with Prof. Alireza Entezari while pursuing his Ph.D. After his graduation, he worked as an application support engineer under the supervision of Robijn Hage in MathWorks, Inc., the developer of the leading computing software MATLAB. His primary research interests are in uncertainty quantification and statistical analysis.

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