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Computer Vision and Robotics

Proceedings of CVR 2023

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Praveen Kumar Shukla

    1. Department of Computer Science and Engineering, Babu Banarasi Das University, Lucknow, India

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  2. Himanshu Mittal

    1. Department of Artificial Intelligence and Data Sciences, Indira Gandhi Delhi Technical University for Women, New Delhi, India

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  3. Andries Engelbrecht

    1. Department of Industrial Engineering and Computer Science Division, University of Stellenbosch, Stellenbosch, South Africa

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  • Discusses the outcomes of CVR 2023, held in Lucknow, India, during February 2023
  • Presents recent research in computer vision and robotics
  • Serves as a reference guide for researchers and practitioners in academia and industry

Part of the book series: Algorithms for Intelligent Systems (AIS)

Included in the following conference series:

Conference proceedings info: CVR 2023.

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Table of contents (46 papers)

  1. Front Matter

    Pages i-xiv
    Download chapter PDF

  2. Rebalancing Algorithm for Bike Sharing System Networks with Uncertain Inventories and Stations with Finite Capacity

    • Juan F. Venegas
    Pages 1-13

  3. Sensor-Based Personal Activity Recognition Using Mixed 5-Layer CNN-LSTM and Hyperparameter Tunning

    • Bhagya Rekha Sangisetti, Suresh Pabboju
    Pages 15-26

  4. Machine Learning Approach Using Artificial Neural Networks to Detect Malicious Nodes in IoT Networks

    • Kazi Kutubuddin Sayyad Liyakat
    Pages 27-37

  5. Ensemble Learning Approach for Heart Disease Prediction

    • Pralhad R. Gavali, Siddhi A. Bhosale, Nandini A. Sangar, Sanket R. Patil
    Pages 39-50

  6. Computer Vision-Based Contactless Cardiac Pulse Estimation

    • Mousami Turuk, R. Sreemathy, Shantanu Shinde, Sujay Naik, Shardul Khandekar
    Pages 51-64

  7. Mobile Malware Detection: A Comparative Study of Machine Learning Models

    • S. Shaambhavi, M. Murale Manohar, M. Vijayalakshmi
    Pages 65-75

  8. Distance and Similarity Measures of Hesitant Bi-Fuzzy Set and Its Applications in Pattern Recognition Problem

    • Soniya Gupta, Dheeraj Kumar Joshi, Natasha Awasthi, Shshank Chaube, Bhagwati Joshi
    Pages 77-91

  9. Impact of Machine Learning in Education

    • Hiral M. Patel, Rupal R. Chaudhari, Krunal Suthar, Manish V. Patel, Ravi R. Patel, Ankur J. Goswami
    Pages 93-106

  10. Lung Disease Classification Using CNN

    • G. S. Anushia, S. Hema
    Pages 107-116

  11. Facemask Detection Using Convolutional Neural Networks

    • J. Viswanathan, Elangovan Guruva Reddy, R. Viswanathan
    Pages 117-129

  12. Optimized Encryption Technique for Securing E-Health Images

    • Kiran, D. S. Sunil Kumar, K. N. Bharath, J. Yashwanth, Bharathesh N. Patel, K. Prabhavathi
    Pages 131-141

  13. Machine Learning Approach for Traffic Sign Detection and Indication Using Open CV with Python

    • Kothapalli Phani Varma, Yadavalli S. S. Sriramam, Chalapathiraju Kanumuri, A. Harish Varma, Cheruku Sri Harsha
    Pages 143-150

  14. Determining the Fruit Ripening Stage Using Convolution Neural Networks

    • K. Lakshmi Divya, M. Krishnapriya, Bh. Maheedhar, K. Satyanarayana Raju
    Pages 151-159

  15. Text Preprocessing and Enrichment of Large Text Corpus-Based Keyphrase Generation for Goal-Oriented Dialogue Systems

    • Jimmy Jose, Beaulah P. Soundarabai
    Pages 161-181

  16. Investigating Land Use and Land Cover Classification Using Landsat-8 Remote Sensing Data by Comparing Machine Learning Algorithms (Case Study: Dehradun Region)

    • Gunjan Dourbi, Bharti Kalra, Sandeep Kumar
    Pages 183-196

  17. A Comprehensive Review and Discussion on Corn Leaf Disease Detection Using Artificial Intelligence

    • K. Giri Babu, G. Sandhya, K. Deepthi Reddy
    Pages 197-205

  18. SESC-YOLO: Enhanced YOLOV5 for Detecting Defects on Steel Surface

    • S. Kavitha, K. R. Baskaran, K. Santhiya
    Pages 207-216

  19. Real-Time Drowning Detection at the Edge

    • Huy Hoang Nguyen, Xuan Loc Ngo
    Pages 217-229

  20. Technical Review on Early Diagnosis of Types of Glaucoma Using Multi Feature Analysis Based on DBN Classification

    • Likhitha Sunkara, Bhargavi Lahari Vema, Hema Lakshmi Prasanna Rajulapati, Avinash Mukkapati, V. B. K. L. Aruna
    Pages 231-241
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  1. Computer Vision and Robotics

Keywords

About this book

This book consists of a collection of the high-quality research articles in the field of computer vision and robotics which are presented in the International Conference on Computer Vision and Robotics (CVR 2023), organized by BBD University Lucknow, India, during 24–25 February 2023. The book discusses applications of computer vision and robotics in the fields like medical science, defence, and smart city planning. The book presents recent works from researchers, academicians, industry, and policy makers.

Editors and Affiliations

  • Department of Computer Science and Engineering, Babu Banarasi Das University, Lucknow, India

    Praveen Kumar Shukla

  • Department of Artificial Intelligence and Data Sciences, Indira Gandhi Delhi Technical University for Women, New Delhi, India

    Himanshu Mittal

  • Department of Industrial Engineering and Computer Science Division, University of Stellenbosch, Stellenbosch, South Africa

    Andries Engelbrecht

About the editors

Prof. Praveen Kumar Shukla is presently working as a Professor and Head in the department of Computer Science & Engineering, Babu Banarasi Das University, Lucknow. He is Ph. D. in Computer Science & Engineering from Dr. A P J Abdul Kalam Technical University, Lucknow. He is B. Tech in Information Technology and M. Tech. in Computer Science & Engineering. His research area includes Fuzzy Systems (Interval Type-2 Fuzzy Systems and Type-2 Fuzzy Systems), Evolutionary Algorithms (Genetic Algorithms), Genetic Fuzzy Systems, Multi-Objective Optimization using Evolutionary Algorithms, Big Data Analytics and Internet of Things. He has published many Papers in National Conferences, International Conferences and International Journals. He has also published a book “Introduction to Information Security and Cyber Laws” in 2014 with Dreamtech Publishers and published a patent on “Social Media based Framework for Community Moblisation during and post Pandemic” in 2021.He completed one Research Project on “Particle Swarm Optimization Based Electric Load Forecasting” sponsored by Dr. APJ Abdul Kalam Technical University under TEQIP-III scheme. He is the member of IEEE (Computational Intelligence Society), USA, International Association of Computer Science and Information Technology (IACSIT), Singapore, International Association of Engineers (IAENG), Hong Kong, Society of Digital Information and Wireless Communications (SDIWC), Institutions of Engineers, India and Soft Computing Research Society (SCRS), India.

Dr. Himanshu Mittal is an Assistant Professor in the Department of Artificial Intelligence and Data Sciences, Indira Gandhi Delhi Technical University for Women, India. Prior to this, he was working as an Assistant Professor in the Computer Science Department of Jaypee Institute of Information Technology, India. He received his Ph.D. in the field of computer vision under the supervision of Dr. Mukesh Saraswat. The keen research areas of Dr. Mittal are image analysis, machine learning, and evolutionary algorithms. He has an excellent academic record as well as a research background with papers in reputed journals including IEEE Transactions. Also, he has been the co-principal investigator of the research project funded by the Science and Engineering Research Board, Department of Science and Technology, India. Dr. Mittal is also a reviewer of many International Journals and Conferences.

Prof. Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artificial Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.

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