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Machine Learning and Metaheuristics Algorithms, and Applications

Second Symposium, SoMMA 2020, Chennai, India, October 14–17, 2020, Revised Selected Papers

  • Conference proceedings
  • © 2021

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Editors:
  1. Sabu M. Thampi

    1. Indian Institute of Information Technology and Management - Kerala, Trivandrum, India

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  2. Selwyn Piramuthu

    1. University of Florida, Gainesville, USA

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  3. Kuan-Ching Li

    1. Providence University, Taichung, Taiwan

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  4. Stefano Berretti

    1. Università degli Studi di Firenze, Florence, Italy

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  5. Michal Wozniak

    1. Wrocław University of Technology, Wrocław, Poland

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  6. Dhananjay Singh

    1. Hankuk University of Foreign Studies, Yongin, Korea (Republic of)

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Part of the book series: Communications in Computer and Information Science (CCIS, volume 1366)

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Conference proceedings info: SoMMA 2020.

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About this book

This book constitutes the refereed proceedings of the Second Symposium on Machine Learning and Metaheuristics Algorithms, and Applications, SoMMA 2020, held in Chennai, India, in October 2020. Due to the COVID-19 pandemic the conference was held online. 

The 12 full papers and 7 short papers presented in this volume were thoroughly reviewed and selected from 40 qualified submissions. The papers cover such topics as machine learning, artificial intelligence, Internet of Things, modeling and simulation, disctibuted computing methodologies, computer graphics, etc. 

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Table of contents (19 papers)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Learning 3DMM Deformation Coefficients for Action Unit Detection

    • Luigi Ariano, Claudio Ferrari, Stefano Berretti
    Pages 1-14

  3. Smart Security and Surveillance System in Laboratories Using Machine Learning

    • Ashwini Patil, Krupali Shetty, Shweta Hinge, G. Tejaswini, V. Anni Shinay, Suneeta V. Budihal et al.
    Pages 15-28

  4. Deep Neural Networks with Multi-class SVM for Recognition of Cross-Spectral Iris Images

    • Mulagala Sandhya, Ujas Rudani, Dilip Kumar Vallabhadas, Mulagala Dileep, Sriramulu Bojjagani, Sravya Pallantla et al.
    Pages 29-41

  5. Gaze Fusion-Deep Neural Network Model for Glaucoma Detection

    • Sajitha Krishnan, J. Amudha, Sushma Tejwani
    Pages 42-53

  6. Deep Learning Based Stable and Unstable Candle Flame Detection

    • Amir Khan, Mohammad Samar Ansari
    Pages 54-62

  7. Emotion Recognition from Facial Expressions Using Siamese Network

    • Naga Venkata Sesha Saiteja Maddula, Lakshmi R. Nair, Harshith Addepalli, Suja Palaniswamy
    Pages 63-72

  8. Activity Modeling of Individuals in Domestic Households Using Fuzzy Logic

    • Sristi Ram Dyuthi, Shahid Mehraj Shah
    Pages 73-87

  9. Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models

    • Sidra Mehtab, Jaydip Sen, Abhishek Dutta
    Pages 88-106

  10. An Improved Salp Swarm Algorithm Based on Adaptive \(\upbeta \)-Hill Climbing for Stock Market Prediction

    • Abhishek Kumar, Rishesh Garg, Arnab Anand, Ram Sarkar
    Pages 107-121

  11. Data Driven Methods for Finding Pattern Anomalies in Food Safety

    • S. Anantha Krishna, Amal Soman, Manjusha Nair
    Pages 122-130

  12. Exam Seating Allocation to Prevent Malpractice Using Genetic Multi-optimization Algorithm

    • Madhav M. Kashyap, S. Thejas, C. G. Gaurav, K. S. Srinivas
    Pages 131-145

  13. Big Data: Does BIG Matter for Your Business?

    • Wei Zhou, Selwyn Piramuthu
    Pages 146-156

  14. Modelling Energy Consumption of Domestic Households via Supervised and Unsupervised Learning: A Case Study

    • Shahid Mehraj Shah
    Pages 157-171

  15. Machine Learning and Soft Computing Techniques for Combustion System Diagnostics and Monitoring: A Survey

    • Amir Khan, Mohd. Zihaib Khan, Mohammad Samar Ansari
    Pages 172-186

  16. Traffic Sign Classification Using ODENet

    • Yaratapalli Nitheesh Chandra Sainath, Reethesh Venkataraman, Abhishek Dinesan, Ashni Manish Bhagvandas, Padmamala Sriram
    Pages 187-197

  17. Analysis of UNSW-NB15 Dataset Using Machine Learning Classifiers

    • Anne Dickson, Ciza Thomas
    Pages 198-207

  18. Concept Drift Detection in Phishing Using Autoencoders

    • Aditya Gopal Menon, Gilad Gressel
    Pages 208-220

  19. Detection of Obfuscated Mobile Malware with Machine Learning and Deep Learning Models

    • K. A. Dhanya, O. K. Dheesha, T. Gireesh Kumar, P. Vinod
    Pages 221-231

  20. CybSecMLC: A Comparative Analysis on Cyber Security Intrusion Detection Using Machine Learning Classifiers

    • Sriramulu Bojjagani, B. Ramachandra Reddy, Mulagala Sandhya, Dinesh Reddy Vemula
    Pages 232-245
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Other volumes

  1. Machine Learning and Metaheuristics Algorithms, and Applications

Editors and Affiliations

  • Indian Institute of Information Technology and Management - Kerala, Trivandrum, India

    Sabu M. Thampi

  • University of Florida, Gainesville, USA

    Selwyn Piramuthu

  • Providence University, Taichung, Taiwan

    Kuan-Ching Li

  • Università degli Studi di Firenze, Florence, Italy

    Stefano Berretti

  • Wrocław University of Technology, Wrocław, Poland

    Michal Wozniak

  • Hankuk University of Foreign Studies, Yongin, Korea (Republic of)

    Dhananjay Singh

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