World's Best Scientists 2026 revealed!

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Computer Science

D-Index
43
Citations
14960
World Ranking
7762
National Ranking
315

Overview

Paul Fieguth is affiliated with the University of Waterloo in Canada and has a significant research presence in the fields of computer science and engineering. Their work spans multiple subfields including computer vision and pattern recognition, biomedical engineering, artificial intelligence, mechanics of materials, and mechanical engineering.

The scientist has focused research efforts on topics such as photoacoustic and ultrasonic imaging, thermography and photoacoustic techniques, optical measurement and interference techniques, advanced image and video retrieval techniques, optical coherence tomography applications, advanced neural network applications, and advanced vision and imaging.

Frequent publication venues for their work include arXiv (Cornell University), with 24 publications, followed by the Journal of Computational Vision and Imaging Systems with 6 publications, Scientific Reports with 5, Zenodo (CERN European Organization for Nuclear Research) with 4, and IEEE Access with 4.

Paul Fieguth has collaborated extensively with colleagues such as Parsin Haji Reza, Nicholas Pellegrino, Benjamin R. Ecclestone, Mohamed A. Naiel, and Amir Nazemi, with joint publications numbering 18, 18, 12, 11, and 10 respectively.

Recent papers authored or co-authored by Paul Fieguth include:

  • A review of uncertainty quantification in deep learning: Techniques, applications and challenges, 2021, Information Fusion
  • Deep Learning for Instance Retrieval: A Survey, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • A new concordant partial AUC and partial c statistic for imbalanced data in the evaluation of machine learning algorithms, 2020, BMC Medical Informatics and Decision Making
  • Virtual histological staining of label-free total absorption photoacoustic remote sensing (TA-PARS), 2022, Scientific Reports
  • Process performance evaluation and classification via in-situ melt pool monitoring in directed energy deposition, 2021, CIRP Journal of Manufacturing Science and Technology

Best Publications

  • Deep Learning for Generic Object Detection: A Survey

    Li Liu;Li Liu;Wanli Ouyang;Xiaogang Wang;Paul W. Fieguth

  • A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges

    Moloud Abdar;Farhad Pourpanah;Sadiq Hussain;Dana Rezazadegan

  • A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure

    Christian Koch;Kristina Georgieva;Varun Kasireddy;Burcu Akinci

  • Median Robust Extended Local Binary Pattern for Texture Classification

    Li Liu;Songyang Lao;Paul W. Fieguth;Yulan Guo

  • Color-based tracking of heads and other mobile objects at video frame rates

    P. Fieguth;D. Terzopoulos

  • Local binary features for texture classification

    Li Liu;Paul Fieguth;Yulan Guo;Xiaogang Wang

  • Extended local binary patterns for texture classification

    Li Liu;Lingjun Zhao;Yunli Long;Gangyao Kuang

  • Texture Classification from Random Features

    Li Liu;Paul Fieguth

  • From BoW to CNN: Two Decades of Texture Representation for Texture Classification

    Li Liu;Li Liu;Jie Chen;Paul W. Fieguth;Guoying Zhao

  • Automated detection of cracks in buried concrete pipe images

    Sunil K. Sinha;Paul W. Fieguth

  • Median robust extended local binary pattern for texture classification

    Li Liu;Paul Fieguth;Matti Pietikainen;Songyang Lao

  • BRINT: Binary Rotation Invariant and Noise Tolerant Texture Classification

    Li Liu;Yunli Long;Paul W. Fieguth;Songyang Lao

  • Deep Learning for Instance Retrieval: A Survey

    Unknown

  • Adaptive Wiener filtering of noisy images and image sequences

    F. Jin;P. Fieguth;L. Winger;E. Jernigan

  • Multiresolution optimal interpolation and statistical analysis of TOPEX/POSEIDON satellite altimetry

    Paul W. Fieguth;William C. Karl;Alan S. Willsky;Carl Wunsch

  • Extended local binary patterns for face recognition

    Li Liu;Paul Fieguth;Guoying Zhao;Matti Pietikäinen

  • Automatic Skin Lesion Segmentation via Iterative Stochastic Region Merging

    A. Wong;J. Scharcanski;P. Fieguth

  • Segmentation of buried concrete pipe images

    Sunil K. Sinha;Paul W. Fieguth

  • A new concordant partial AUC and partial c statistic for imbalanced data in the evaluation of machine learning algorithms

    André M. Carrington;Paul W. Fieguth;Hammad Qazi;Andreas Holzinger;Andreas Holzinger

  • Statistical Image Processing and Multidimensional Modeling

    Paul Fieguth

  • Neuro-fuzzy network for the classification of buried pipe defects

    Sunil K. Sinha;Paul W. Fieguth

  • Decoupled Active Contour (DAC) for Boundary Detection

    Akshaya Kumar Mishra;Paul W Fieguth;David A Clausi

Frequent Co-Authors

Alexander Wong
Alexander Wong University of Waterloo
David A. Clausi
David A. Clausi University of Waterloo
Matti Pietikäinen
Matti Pietikäinen University of Oulu
William Clement Karl
William Clement Karl Boston University
Gangyao Kuang
Gangyao Kuang National University of Defense Technology
Guoying Zhao
Guoying Zhao University of Oulu
Xiaogang Wang
Xiaogang Wang Chinese University of Hong Kong
Carl Wunsch
Carl Wunsch Harvard University
Maria Anna Polak
Maria Anna Polak University of Waterloo

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