Paul Miller

9.0k total citations · 2 hit papers
265 papers, 6.1k citations indexed

About

Paul Miller is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Artificial Intelligence. According to data from OpenAlex, Paul Miller has authored 265 papers receiving a total of 6.1k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Computer Vision and Pattern Recognition, 46 papers in Cognitive Neuroscience and 45 papers in Artificial Intelligence. Recurrent topics in Paul Miller's work include Neural dynamics and brain function (37 papers), Plant Surface Properties and Treatments (26 papers) and Video Surveillance and Tracking Methods (25 papers). Paul Miller is often cited by papers focused on Neural dynamics and brain function (37 papers), Plant Surface Properties and Treatments (26 papers) and Video Surveillance and Tracking Methods (25 papers). Paul Miller collaborates with scholars based in United Kingdom, United States and Australia. Paul Miller's co-authors include Jesús Martínez del Rincón, Niall McLaughlin, A. Mike Burton, Huiyu Zhou, Donald B. Katz, J. Orson, Nathan Morris, Eric E. Hall, R. J. Froud‐Williams and Peter Hancock and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Physical Review Letters.

In The Last Decade

Paul Miller

251 papers receiving 5.8k citations

Hit Papers

Recurrent Convolutional Network for Video-Based Person Re... 2016 2026 2019 2022 2016 2017 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Paul Miller United Kingdom 37 1.8k 1.4k 839 656 543 265 6.1k
Mark Kramer United States 46 4.3k 2.4× 378 0.3× 404 0.5× 1.2k 1.9× 343 0.6× 250 10.7k
Yuanjie Zheng China 34 1.5k 0.8× 2.4k 1.7× 615 0.7× 1.6k 2.4× 146 0.3× 244 8.9k
Liqing Zhang China 37 1.3k 0.7× 4.2k 2.9× 241 0.3× 998 1.5× 666 1.2× 233 7.6k
Matteo Matteucci Italy 32 798 0.5× 1.0k 0.7× 122 0.1× 722 1.1× 250 0.5× 246 4.0k
D.H. Ballard United States 23 2.9k 1.6× 3.3k 2.3× 103 0.1× 946 1.4× 225 0.4× 64 9.1k
Biswa Sengupta United Kingdom 23 879 0.5× 983 0.7× 151 0.2× 991 1.5× 252 0.5× 36 4.1k
Jan Larsen Norway 84 4.4k 2.5× 541 0.4× 436 0.5× 823 1.3× 1.0k 1.9× 439 25.0k
Vittorio Murino Italy 44 547 0.3× 5.2k 3.6× 289 0.3× 1.8k 2.8× 959 1.8× 380 8.6k
Yong Hu China 44 2.0k 1.1× 363 0.3× 176 0.2× 241 0.4× 307 0.6× 592 8.3k
Gail A. Carpenter United States 39 2.3k 1.3× 2.2k 1.5× 186 0.2× 6.4k 9.7× 1.1k 2.1× 120 11.6k

Countries citing papers authored by Paul Miller

Since Specialization
Citations

This map shows the geographic impact of Paul Miller'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 Miller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Miller more than expected).

Fields of papers citing papers by Paul Miller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paul Miller. 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 Miller. The network helps show where Paul Miller may publish in the future.

Co-authorship network of co-authors of Paul Miller

This figure shows the co-authorship network connecting the top 25 collaborators of Paul Miller. A scholar is included among the top collaborators of Paul Miller 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 Miller. Paul Miller is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Miller, Paul, Sean A. Irvine, Jesús Martínez del Rincón, et al.. (2025). Automated precision weighing: Leveraging 2D video feature analysis and machine learning for live body weight estimation of broiler chickens. Smart Agricultural Technology. 10. 100793–100793. 3 indexed citations
3.
Qiu, Si-Wei, et al.. (2023). Multistability in neural systems with random cross-connections. Biological Cybernetics. 117(6). 485–506. 2 indexed citations
4.
Katz, Donald B., et al.. (2023). Distinct competitive impacts of palatability of taste stimuli on sampling dynamics during a preference test.. Behavioral Neuroscience. 137(5). 289–302. 1 indexed citations
5.
Miller, Paul, et al.. (2022). Coupled Dynamics of Stimulus-Evoked Gustatory Cortical and Basolateral Amygdalar Activity. Journal of Neuroscience. 43(3). 386–404. 1 indexed citations
6.
Katz, Donald B., et al.. (2021). A model of naturalistic decision making in preference tests. PLoS Computational Biology. 17(9). e1009012–e1009012. 3 indexed citations
7.
Paradis, Suzanne, et al.. (2019). Stable memory and computation in randomly rewiring neural networks. Journal of Neurophysiology. 122(1). 66–80. 13 indexed citations
8.
Shlaer, Benjamin, et al.. (2019). Spatiotemporal discrimination in attractor networks with short-term synaptic plasticity. Journal of Computational Neuroscience. 46(3). 279–297. 5 indexed citations
9.
Miller, Paul & Jonathan Cannon. (2018). Combined mechanisms of neural firing rate homeostasis. Biological Cybernetics. 113(1-2). 47–59. 10 indexed citations
10.
Okada, Yoshio, Matti Hämäläinen, Kevin Pratt, et al.. (2016). BabyMEG: A whole-head pediatric magnetoencephalography system for human brain development research. Review of Scientific Instruments. 87(9). 94301–94301. 56 indexed citations
11.
Sadacca, Brian F, et al.. (2016). The Behavioral Relevance of Cortical Neural Ensemble Responses Emerges Suddenly. Journal of Neuroscience. 36(3). 655–669. 39 indexed citations
12.
Johnson, W. Brad, et al.. (2015). Undergraduate Research Mentoring: Obstacles and Opportunities. Mentoring & Tutoring Partnership in Learning. 23(5). 441–453. 23 indexed citations
13.
Vandermaas­-Peeler, Maureen, et al.. (2015). “Mentoring is Sharing the Excitement of Discovery”: Faculty Perceptions of Undergraduate Research Mentoring. Mentoring & Tutoring Partnership in Learning. 23(5). 377–393. 15 indexed citations
14.
Ma, Wenjun, Weiru Liu, Paul Miller, & Xudong Luo. (2014). A game-theoretic approach for threats detection and intervention in surveillance. Adaptive Agents and Multi-Agents Systems. 1565–1566.
15.
Miller, Paul & J. Orson. (2012). Spray drift and buffer zones - a review.. Aspects of applied biology. 165–172. 1 indexed citations
16.
Tuck, C. R., M. C. B. Ellis, Paul Miller, et al.. (2010). An alternative surfactant to nonyl phenol ethoxylates for spray application research.. Aspects of applied biology. 311–316. 1 indexed citations
17.
Jones, Lauren M., Alfredo Fontanini, Brian F Sadacca, Paul Miller, & Donald B. Katz. (2007). Natural stimuli evoke dynamic sequences of states in sensory cortical ensembles. Proceedings of the National Academy of Sciences. 104(47). 18772–18777. 198 indexed citations
18.
Scotford, I.M. & Paul Miller. (2005). Vehicle mounted sensors for estimating tiller density and leaf area index (LAI) of winter wheat. 201–208. 6 indexed citations
19.
Miller, Paul, et al.. (2002). Learning Objects and the Information Environment. Ariadne. 2 indexed citations
20.
Wheeler, Helen C., et al.. (2001). A map-based system for patch spraying weeds - system control. Rothamsted Repository (Rothamsted Repository). 1 indexed citations

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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