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Overview

Suresh Sundaram is affiliated with the Indian Institute of Science in India. Their research primarily spans the field of Computer Science, with a strong focus on Computer Vision and Pattern Recognition and Artificial Intelligence.

The scientist's work covers several specialized subfields including Aerospace Engineering, Automotive Engineering, and Cancer Research. Their research topics include Handwritten Text Recognition Techniques, Advanced Neural Network Applications, and Domain Adaptation and Few-Shot Learning. Other areas of focus are Multimodal Machine Learning Applications, Autonomous Vehicle Technology and Safety, Digital Media Forensic Detection, and Advanced Image and Video Retrieval Techniques.

The following is a selection of recent papers authored or co-authored by Suresh Sundaram:

  • Generative Replay-based Continual Zero-Shot Learning, 2021, arXiv (Cornell University)
  • Siamese-based offline word level writer identification in a reduced subspace, 2023, Engineering Applications of Artificial Intelligence
  • Graph-Based Prediction and Planning Policy Network (GP3Net) for Scalable Self-Driving in Dynamic Environments Using Deep Reinforcement Learning, 2024, Proceedings of the AAAI Conference on Artificial Intelligence
  • Online writer identification system using adaptive sparse representation framework, 2020, IET Biometrics
  • Siamese based Neural Network for Offline Writer Identification on word level data, 2022, arXiv (Cornell University)

Suresh Sundaram frequently collaborates with several co-authors, including Aniruddh Sikdar, Sumanth Udupa, Vineet Kumar, Jayabrata Chowdhury, and N. Sundararajan.

The scientist's works are widely published in noted venues. Key publication outlets include:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Engineering Applications of Artificial Intelligence
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IET Biometrics

The range of Sundaram's work encompasses algorithmic and applied research in areas such as autonomous vehicle safety, neural networks for handwriting recognition, and methods for continual learning and few-shot learning. This multidisciplinary approach integrates techniques from machine learning, deep reinforcement learning, and statistical pattern recognition to address challenges in both academic and practical domains.

Best Publications

  • Reversible Watermarking Algorithm Using Sorting and Prediction

    V. Sachnev;Hyoung Joong Kim;Jeho Nam;S. Suresh

  • Self regulating particle swarm optimization algorithm

    M.R. Tanweer;S. Suresh;N. Sundararajan

  • Multi-UAV Oxyrrhis Marina-Inspired Search and Dynamic Formation Control for Forest Firefighting

    K. Harikumar;J. Senthilnath;Suresh Sundaram

  • Risk-sensitive loss functions for sparse multi-category classification problems

    S. Suresh;N. Sundararajan;P. Saratchandran

  • Meta-cognitive Neural Network for classification problems in a sequential learning framework

    G. Sateesh Babu;S. Suresh

  • A Metacognitive Neuro-Fuzzy Inference System (McFIS) for Sequential Classification Problems

    Kartick Subramanian;Sundaram Suresh;Narasimhan Sundararajan

  • A meta-cognitive sequential learning algorithm for neuro-fuzzy inference system

    K. Subramanian;S. Suresh

  • ICGA-PSO-ELM Approach for Accurate Multiclass Cancer Classification Resulting in Reduced Gene Sets in Which Genes Encoding Secreted Proteins Are Highly Represented

    Saras Saraswathi;Suresh Sundaram;Narasimhan Sundararajan;Michael Zimmermann

  • Metacognitive learning in a fully complex-valued radial basis function neural network

    R. Savitha;S. Suresh;N. Sundararajan

  • Meta-cognitive RBF Network and its Projection Based Learning algorithm for classification problems

    G. Sateesh Babu;S. Suresh

  • An enhanced contextual DTW based system for online signature verification using Vector Quantization

    Abhishek Sharma;Suresh Sundaram

  • A sequential multi-category classifier using radial basis function networks

    S. Suresh;N. Sundararajan;P. Saratchandran

  • Dynamic mentoring and self-regulation based particle swarm optimization algorithm for solving complex real-world optimization problems

    Muhammad Rizwan Tanweer;Sundaram Suresh;N. Sundararajan

  • Identifying differences in brain activities and an accurate detection of autism spectrum disorder using resting state functional-magnetic resonance imaging : A spatial filtering approach.

    Vigneshwaran Subbaraju;Mahanand Belathur Suresh;Suresh Sundaram;Sundararajan Narasimhan

  • Parkinson's disease prediction using gene expression - A projection based learning meta-cognitive neural classifier approach

    G. Sateesh Babu;S. Suresh

  • 2012 Special Issue: A meta-cognitive learning algorithm for a Fully Complex-valued Relaxation Network

    R. Savitha;S. Suresh;N. Sundararajan

  • On the Exploration of Information From the DTW Cost Matrix for Online Signature Verification

    Abhishek Sharma;Suresh Sundaram

  • A Meta-Cognitive Learning Algorithm for an Extreme Learning Machine Classifier

    Ramaswamy Savitha;Sundaram Suresh;H. J. Kim

  • An Evolving Interval Type-2 Neurofuzzy Inference System and Its Metacognitive Sequential Learning Algorithm

    Ankit Kumar Das;Kartick Subramanian;Suresh Sundaram

  • Fast learning Circular Complex-valued Extreme Learning Machine (CC-ELM) for real-valued classification problems

    R. Savitha;S. Suresh;N. Sundararajan

Frequent Co-Authors

S. R. Mahadeva Prasanna
S. R. Mahadeva Prasanna Indian Institute of Technology Dharwad
Narasimhan Sundararajan
Narasimhan Sundararajan Nanyang Technological University
Mahardhika Pratama
Mahardhika Pratama University of South Australia
Narasimalu Srikanth
Narasimalu Srikanth Nanyang Technological University
Debasish Ghose
Debasish Ghose Indian Institute of Science
Igor Škrjanc
Igor Škrjanc University of Ljubljana
Raghu Krishnapuram
Raghu Krishnapuram Indian Institute of Science
Edwin Lughofer
Edwin Lughofer Johannes Kepler University of Linz
Alexandros Iosifidis
Alexandros Iosifidis Aarhus University

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