Paul Fieguth

13.0k total citations · 4 hit papers
225 papers, 8.7k citations indexed

About

Paul Fieguth is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Paul Fieguth has authored 225 papers receiving a total of 8.7k indexed citations (citations by other indexed papers that have themselves been cited), including 137 papers in Computer Vision and Pattern Recognition, 39 papers in Media Technology and 28 papers in Artificial Intelligence. Recurrent topics in Paul Fieguth's work include Medical Image Segmentation Techniques (52 papers), Image and Signal Denoising Methods (34 papers) and Image Retrieval and Classification Techniques (32 papers). Paul Fieguth is often cited by papers focused on Medical Image Segmentation Techniques (52 papers), Image and Signal Denoising Methods (34 papers) and Image Retrieval and Classification Techniques (32 papers). Paul Fieguth collaborates with scholars based in Canada, United States and China. Paul Fieguth's co-authors include Li Liu, Xiaogang Wang, Matti Pietikäinen, Xinwang Liu, Jie Chen, Wanli Ouyang, Sunil K. Sinha, Christian Koch, Hristina Georgieva and Varun Kasireddy and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Paul Fieguth

212 papers receiving 8.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep Learning for Generic Object Detection: A Survey

2019 1.8k citations Li Liu, Paul Fieguth et al. profile →
A review of uncertainty quantification in deep learning: Techniques, applications and challenges

2021 1.5k citations Moloud Abdar, Farhad Pourpanah et al. Information Fusion profile →
A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure

2015 748 citations Paul Fieguth et al. Advanced Engineering Informatics profile →
Median Robust Extended Local Binary Pattern for Texture Classification

2016 306 citations Li Liu, Paul Fieguth et al. IEEE Transactions on Image Processing profile →

Peers

Countries citing papers authored by Paul Fieguth

Since Specialization

Citations

This map shows the geographic impact of Paul Fieguth's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Paul Fieguth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Fieguth more than expected).

Fields of papers citing papers by Paul Fieguth

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paul Fieguth. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Paul Fieguth. The network helps show where Paul Fieguth may publish in the future.

Co-authorship network of co-authors of Paul Fieguth

This figure shows the co-authorship network connecting the top 25 collaborators of Paul Fieguth. A scholar is included among the top collaborators of Paul Fieguth based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Paul Fieguth. Paul Fieguth is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Challenges for Predictive Modeling With Neural Network Techniques Using Error‐Prone Dietary Intake Data 2025 ·Statistics in Medicine ·(unknown), (unknown), (unknown), Paul Fieguth, Sharon I. Kirkpatrick, Michael B. Wallace, Kevin W. Dodd	0
2	Uncertainty-Aware δ-GLMB Filtering for Multi-Target Tracking 2025 ·Big Data and Cognitive Computing ·(unknown), Saed Moradi, Zohreh Azimifar, Paul Fieguth	0
3	Defect detection on multi-type rail surfaces via IoU decoupling and multi-information alignment 2024 ·Advanced Engineering Informatics ·(unknown), Paul Fieguth, Ziji Ma, (unknown), Hongli Liu	5
4	Domain-Guided Spatio-Temporal Self-Attention for Egocentric 3D Pose Estimation 2023 ·Jinman Park, (unknown), (unknown), (unknown), Sirisha Rambhatla, Paul Fieguth	6
5	Time-domain feature extraction for target-specificity in Photoacoustic Remote Sensing Microscopy 2022 ·arXiv (Cornell University) ·(unknown), (unknown), Paul Fieguth, Parsin Haji Reza	5
6	A review of uncertainty quantification in deep learning: Techniques, applications and challenges breakdown → 2021 ·Information Fusion ·Moloud Abdar, Farhad Pourpanah, Sadiq Hussain, Dana Rezazadegan, Li Liu, Mohammad Ghavamzadeh, Paul Fieguth, Xiaochun Cao, Abbas Khosravi, U. Rajendra Acharya, Vladimir Makarenkov, Saeid Nahavandi	1491
7	Adaptive vision-based detection of laser-material interaction for directed energy deposition 2020 ·Additive manufacturing ·Mohamed A. Naiel, (unknown), Mihaela Vlasea, Paul Fieguth	19
8	Texture classification in extreme scale variations using GANet 2019 ·University of Oulu Repository (University of Oulu) ·Li Liu, Jie Chen, Guoying Zhao, Paul Fieguth, Xilin Chen, Matti Pietikäinen	22
9	Stage-wise Training: An Improved Feature Learning Strategy for Deep Models 2015 ·Neural Information Processing Systems ·Elnaz Barshan, Paul Fieguth	11
10	Homotopic non-local regularized reconstruction from sparse positron emission tomography measurements 2015 ·BMC Medical Imaging ·Alexander Wong, Chenyi Liu, Xiaoyu Wang, Paul Fieguth, (unknown)	2
11	Comparison of Corneal Thickness Measured with Swept Source Anterior Segment Optical Coherence Tomographer, Pentacam and Ultrasound 2014 ·Investigative Ophthalmology & Visual Science ·(unknown), (unknown), (unknown), (unknown), Alex Wong, Paul Fieguth, Luigina Sorbara, Kostadinka Bizheva	1
12	Homotopic, non-local sparse reconstruction of optical coherence tomography imagery 2012 ·Optics Express ·Chenyi Liu, Alexander Wong, Kostadinka Bizheva, Paul Fieguth, (unknown)	17
13	Automatic Skin Lesion Segmentation via Iterative Stochastic Region Merging 2011 ·IEEE Transactions on Information Technology in Biomedicine ·Alexander Wong, Jacob Scharcanski, Paul Fieguth	107
14	Sparse Reconstruction of Breast MRI Using Homotopic <formula formulatype="inline"><tex Notation="TeX">$L_0$</tex></formula> Minimization in a Regional Sparsified Domain 2010 ·IEEE Transactions on Biomedical Engineering ·Alexander Wong, Akshaya Mishra, Paul Fieguth, David A. Clausi	27
15	A probabilistic cell model in background corrected image sequences for single cell analysis 2010 ·BioMedical Engineering OnLine ·Nezamoddin N. Kachouie, Paul Fieguth, Eric Jervis	3
16	CPOL: Complex phase order likelihood as a similarity measure for MR–CT registration 2009 ·Medical Image Analysis ·Alexander Wong, David A. Clausi, Paul Fieguth	15
17	Improved interactive medical image segmentation using Enhanced Intelligent Scissors (EIS) 2008 ·PubMed ·Akshaya Mishra, Alexander Wong, (unknown), David A. Clausi, Paul Fieguth	26
18	Hierarchical Region Mean-Based Image Segmentation 2006 ·Slawomir Wesolkowski, Paul Fieguth	2
19	Hierarchical Markov models for wavelet-domain statistics 2003 ·Zohreh Azimifar, Paul Fieguth, (unknown)	3
20	Multiscale methods for the segmentation and reconstruction of signals and images 2000 ·IEEE Transactions on Image Processing ·(unknown), Paul Fieguth, W.C. Karl, Alan S. Willsky	24

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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