World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
5678
World Ranking
10776
National Ranking
4490

Overview

Sheryl Brahnam is affiliated with Missouri State University in the United States. Their primary research domain falls within Computer Science, with a strong focus on multiple subfields including Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology, Signal Processing, and Media Technology.

Their work covers various specialized topics such as Advanced Image and Video Retrieval Techniques, Animal Vocal Communication and Behavior, Advanced Neural Network Applications, Music and Audio Processing, Remote-Sensing Image Classification, Machine Learning and Data Classification, and Neural Networks and Applications.

Frequent co-authors of Sheryl Brahnam include:

  • Loris Nanni
  • Alessandra Lumini
  • Gianluca Maguolo
  • Michelangelo Paci
  • Andrea Loreggia

The scientist has published extensively in several venues. Common publication venues include:

  • Preprints.org
  • arXiv (Cornell University)
  • Applied Sciences
  • Journal of Imaging
  • Sensors

Some recent papers authored or co-authored by Sheryl Brahnam are listed below:

  • High performing ensemble of convolutional neural networks for insect pest image detection, 2021, Ecological Informatics
  • An Ensemble of Convolutional Neural Networks for Audio Classification, 2021, MDPI (MDPI AG)
  • Comparison of Different Image Data Augmentation Approaches, 2021, Journal of Imaging
  • Comparison of Transfer Learning and Conventional Machine Learning Applied to Structural Brain MRI for the Early Diagnosis and Prognosis of Alzheimer's Disease, 2020, Frontiers in Neurology
  • Ensemble of convolutional neural networks to improve animal audio classification, 2020, EURASIP Journal on Audio Speech and Music Processing

In addition, Sheryl Brahnam has contributed to book publications, including a title published by Springer Nature:

  • Recent Advances in Technologies for Inclusive Well-Being, 2021

Best Publications

  • Local binary patterns variants as texture descriptors for medical image analysis

    Loris Nanni;Alessandra Lumini;Sheryl Brahnam

  • Handcrafted vs. non-handcrafted features for computer vision classification

    Loris Nanni;Stefano Ghidoni;Sheryl Brahnam

  • Survey on LBP based texture descriptors for image classification

    Loris Nanni;Alessandra Lumini;Sheryl Brahnam

  • Local Binary Patterns: New Variants and Applications

    Sheryl Brahnam;Lakhmi C. Jain;Loris Nanni;Alessandra Lumini

  • Gender affordances of conversational agents

    Sheryl Brahnam;Antonella De Angeli

  • Machine recognition and representation of neonatal facial displays of acute pain

    Sheryl Brahnam;Chao-Fa Chuang;Frank Y. Shih;Melinda R. Slack

  • A local approach based on a Local Binary Patterns variant texture descriptor for classifying pain states

    Loris Nanni;Sheryl Brahnam;Alessandra Lumini

  • I hate you! Disinhibition with virtual partners

    Antonella De Angeli;Sheryl Brahnam

  • Wavelet images and Chou’s pseudo amino acid composition for protein classification

    Loris Nanni;Sheryl Brahnam;Alessandra Lumini

  • Machine assessment of neonatal facial expressions of acute pain

    Sheryl Brahnam;Chao-Fa Chuang;Randall S. Sexton;Frank Y. Shih

  • Different approaches for extracting information from the co-occurrence matrix.

    Loris Nanni;Sheryl Brahnam;Stefano Ghidoni;Emanuele Menegatti

  • Prediction of protein structure classes by incorporating different protein descriptors into general Chou's pseudo amino acid composition.

    Loris Nanni;Sheryl Brahnam;Alessandra Lumini

  • Ensemble of convolutional neural networks for bioimage classification

    Loris Nanni;Stefano Ghidoni;Sheryl Brahnam

  • High performing ensemble of convolutional neural networks for insect pest image detection

    Loris Nanni;Alessandro Manfe;Gianluca Maguolo;Alessandra Lumini

  • Introduction to Neonatal Facial Pain Detection Using Common and Advanced Face Classification Techniques

    Sheryl Brahnam;Loris Nanni;Randall S. Sexton

  • An ensemble of convolutional neural networks for audio classification

    Loris Nanni;Gianluca Maguolo;Sheryl Brahnam;Michelangelo Paci

  • Combining visual and acoustic features for audio classification tasks

    L. Nanni;Y.M.G. Costa;D.R. Lucio;C.N. Silla

  • Comparison of Different Image Data Augmentation Approaches

    Loris Nanni;Michelangelo Paci;Sheryl Brahnam;Alessandra Lumini

  • A classifier ensemble approach for the missing feature problem

    Loris Nanni;Alessandra Lumini;Sheryl Brahnam

  • A simple method for improving local binary patterns by considering non-uniform patterns

    Loris Nanni;Sheryl Brahnam;Alessandra Lumini

  • Comparison of Transfer Learning and Conventional Machine Learning Applied to Structural Brain MRI for the Early Diagnosis and Prognosis of Alzheimer's Disease.

    Loris Nanni;Matteo Interlenghi;Sheryl Brahnam;Christian Salvatore

  • An Empirical Study of Different Approaches for Protein Classification

    Loris Nanni;Alessandra Lumini;Sheryl Brahnam

  • Advanced Computational Intelligence Paradigms in Healthcare 6. Virtual Reality in Psychotherapy, Rehabilitation, and Assessment

    Sheryl Brahnam;Lakhmi C. Jain

Frequent Co-Authors

Loris Nanni
Loris Nanni University of Padua
Alessandra Lumini
Alessandra Lumini University of Bologna
Lakhmi C. Jain
Lakhmi C. Jain University of South Australia
Frank Y. Shih
Frank Y. Shih New Jersey Institute of Technology
Antonella De Angeli
Antonella De Angeli Free University of Bozen-Bolzano
Jari Hyttinen
Jari Hyttinen Tampere University
Alan Dix
Alan Dix Swansea University
Christoph Bartneck
Christoph Bartneck University of Canterbury
Simone Bianco
Simone Bianco University of Milano-Bicocca

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