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Computer Science

D-Index
64
Citations
12759
World Ranking
2653
National Ranking
21

Research.com Recognitions

  • 2022 - IEEE Fellow For contributions to secure biometric recognition.
  • 2017 - ACM Senior Member

Overview

Mayank Vatsa is affiliated with the Indian Institute of Technology Jodhpur in India, specializing in the field of computer science. Their research spans multiple subfields including computer vision and pattern recognition, artificial intelligence, signal processing, radiology, nuclear medicine and imaging, and safety research.

The primary research topics explored by Mayank Vatsa include:

  • Face recognition and analysis
  • Biometric identification and security
  • Adversarial robustness in machine learning
  • Face and expression recognition
  • Anomaly detection techniques and applications
  • Digital media forensic detection
  • Generative adversarial networks and image synthesis

Mayank Vatsa has contributed to over 200 publications, with significant frequencies in venues such as:

  • arXiv (Cornell University)
  • IEEE Transactions on Biometrics Behavior and Identity Science
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)
  • Pattern Recognition

Frequent co-authors collaborating with Mayank Vatsa include:

  • Richa Singh
  • Akshay Agarwal
  • Nalini Ratha
  • Surbhi Mittal
  • Puspita Majumdar

Recent publications by Mayank Vatsa demonstrate a focus on biometric security, medical imaging, robustness of machine learning models, and digital forensics:

  • Image Transformation based Defense Against Adversarial Perturbation on Deep Learning Models, 2020, IEEE Transactions on Dependable and Secure Computing
  • AI-based radiodiagnosis using chest X-rays: A review, 2023, Frontiers in Big Data
  • On Matching Finger-Selfies Using Deep Scattering Networks, 2020, IEEE Transactions on Biometrics Behavior and Identity Science
  • On AI Approaches for Promoting Maternal and Neonatal Health in Low Resource Settings: A Review, 2022, Frontiers in Public Health
  • Motion Magnified 3-D Residual-in-Dense Network for DeepFake Detection, 2022, IEEE Transactions on Biometrics Behavior and Identity Science

Mayank Vatsa received recognition including:

  • IEEE Fellow in 2022 for contributions to secure biometric recognition
  • ACM Senior Member since 2017

Best Publications

  • A Robust Skin Color Based Face Detection Algorithm

    Sanjay Kr. Singh;D. S. Chauhan;Mayank Vatsa;Richa Singh

  • Improving Iris Recognition Performance Using Segmentation, Quality Enhancement, Match Score Fusion, and Indexing

    M. Vatsa;R. Singh;A. Noore

  • Computationally Efficient Face Spoofing Detection with Motion Magnification

    Samarth Bharadwaj;Tejas I. Dhamecha;Mayank Vatsa;Richa Singh

  • Plastic Surgery: A New Dimension to Face Recognition

    Richa Singh;Mayank Vatsa;Himanshu S Bhatt;Samarth Bharadwaj

  • Integrated multilevel image fusion and match score fusion of visible and infrared face images for robust face recognition

    Richa Singh;Mayank Vatsa;Afzel Noore

  • Periocular biometrics: When iris recognition fails

    Samarth Bharadwaj;Himanshu S. Bhatt;Mayank Vatsa;Richa Singh

  • Deep dictionary learning

    Snigdha Tariyal;Angshul Majumdar;Richa Singh;Mayank Vatsa

  • Unraveling the Effect of Textured Contact Lenses on Iris Recognition

    Daksha Yadav;Naman Kohli;James S. Doyle;Richa Singh

  • Memetically Optimized MCWLD for Matching Sketches With Digital Face Images

    H. S. Bhatt;S. Bharadwaj;R. Singh;M. Vatsa

  • Unravelling Robustness of Deep Learning Based Face Recognition Against Adversarial Attacks

    Gaurav Goswami;Nalini K. Ratha;Akshay Agarwal;Richa Singh

  • Detecting Silicone Mask-Based Presentation Attack via Deep Dictionary Learning

    Ishan Manjani;Snigdha Tariyal;Mayank Vatsa;Richa Singh

  • LivDet iris 2017 — Iris liveness detection competition 2017

    David Yambay;Benedict Becker;Naman Kohli;Daksha Yadav

  • Biometric quality: a review of fingerprint, iris, and face

    Samarth Bharadwaj;Mayank Vatsa;Richa Singh

  • Recognizing Surgically Altered Face Images Using Multiobjective Evolutionary Algorithm

    H. S. Bhatt;S. Bharadwaj;R. Singh;M. Vatsa

  • Detecting Facial Retouching Using Supervised Deep Learning

    Aparna Bharati;Richa Singh;Mayank Vatsa;Kevin W. Bowyer

  • Recognizing disguised faces: human and machine evaluation.

    Tejas Indulal Dhamecha;Richa Singh;Mayank Vatsa;Ajay Kumar

  • Face recognition with disguise and single gallery images

    Richa Singh;Mayank Vatsa;Afzel Noore

  • On RGB-D face recognition using Kinect

    Gaurav Goswami;Samarth Bharadwaj;Mayank Vatsa;Richa Singh

  • A Mosaicing Scheme for Pose-Invariant Face Recognition

    R. Singh;M. Vatsa;A. Ross;A. Noore

  • Face anti-spoofing using Haralick features

    Akshay Agarwal;Richa Singh;Mayank Vatsa

  • Ocular biometrics

    Ishan Nigam;Mayank Vatsa;Richa Singh

  • Recognizing surgically altered face images

    Himanshu S Bhatt;Samarth Bharadwaj;Richa Singh;Mayank Vatsa

Frequent Co-Authors

Richa Singh
Richa Singh Indian Institute of Technology Jodhpur
Afzel Noore
Afzel Noore Texas A&M University – Kingsville
Angshul Majumdar
Angshul Majumdar Indraprastha Institute of Information Technology Delhi
Arun Ross
Arun Ross Michigan State University
Nalini K. Ratha
Nalini K. Ratha University at Buffalo, State University of New York
Kevin W. Bowyer
Kevin W. Bowyer University of Notre Dame
Anil K. Jain
Anil K. Jain Michigan State University
Massimo Tistarelli
Massimo Tistarelli University of Sassari
Ajay Kumar
Ajay Kumar Hong Kong Polytechnic University

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