Peter Naylor

1.2k total citations · 1 hit paper
28 papers, 723 citations indexed

About

Peter Naylor is a scholar working on Ocean Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Peter Naylor has authored 28 papers receiving a total of 723 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Ocean Engineering, 13 papers in Mechanical Engineering and 6 papers in Mechanics of Materials. Recurrent topics in Peter Naylor's work include Hydraulic Fracturing and Reservoir Analysis (13 papers), Reservoir Engineering and Simulation Methods (11 papers) and Enhanced Oil Recovery Techniques (10 papers). Peter Naylor is often cited by papers focused on Hydraulic Fracturing and Reservoir Analysis (13 papers), Reservoir Engineering and Simulation Methods (11 papers) and Enhanced Oil Recovery Techniques (10 papers). Peter Naylor collaborates with scholars based in United Kingdom, France and Italy. Peter Naylor's co-authors include Thomas Walter, Fabien Reyal, Marick Laé, Caroline A. Stewart, Ian Reid, R.C.A. Pearson, A. J. Drummond, Guillaume Bataillon, Anne Vincent‐Salomon and S. G. Goodyear and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and IEEE Transactions on Medical Imaging.

In The Last Decade

Peter Naylor

23 papers receiving 694 citations

Hit Papers

Segmentation of Nuclei in Histopathology Images by Deep R... 2018 2026 2020 2023 2018 100 200 300
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.

  1. Segmentation of Nuclei in Histopathology Images by Deep Regression of the Distance Map
    2018 397 citations Peter Naylor, Marick Laé et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter Naylor United Kingdom 10 476 319 269 122 97 28 723
Shekoofeh Azizi United States 10 350 0.7× 362 1.1× 333 1.2× 30 0.2× 8 0.1× 25 876
Davood Karimi Canada 14 309 0.6× 176 0.6× 392 1.5× 30 0.2× 5 0.1× 46 795
Getao Du China 8 88 0.2× 131 0.4× 129 0.5× 14 0.1× 22 0.2× 12 441
Salman Khan United States 6 249 0.5× 244 0.8× 299 1.1× 23 0.2× 11 0.1× 18 742
Tran Minh Quan South Korea 12 85 0.2× 240 0.8× 361 1.3× 35 0.3× 13 0.1× 21 733
H.P. Ng Singapore 7 107 0.2× 206 0.6× 92 0.3× 27 0.2× 8 0.1× 17 414
Tarek M. Taha United States 3 193 0.4× 283 0.9× 286 1.1× 18 0.1× 22 0.2× 3 586
Michalis Zervakis Greece 13 188 0.4× 96 0.3× 215 0.8× 22 0.2× 24 0.2× 46 777
Hatice Çınar Akakın Türkiye 7 108 0.2× 241 0.8× 56 0.2× 61 0.5× 9 0.1× 11 416

Countries citing papers authored by Peter Naylor

Since Specialization
Citations

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

Fields of papers citing papers by Peter Naylor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Naylor

This figure shows the co-authorship network connecting the top 25 collaborators of Peter Naylor. A scholar is included among the top collaborators of Peter Naylor 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 Peter Naylor. Peter Naylor 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.
Naylor, Peter, et al.. (2025). Multitemporal Multispectral Dataset for Palaeochannels Segmentation (MAPS). IEEE Access. 13. 203113–203124.
2.
Naylor, Peter, et al.. (2024). Implicit neural representation for change detection. SPIRE - Sciences Po Institutional REpository. 924–934. 1 indexed citations
3.
Ebel, Patrick, Brandon Victor, Peter Naylor, et al.. (2024). Implicit Assimilation of Sparse In Situ Data for Dense & Global Storm Surge Forecasting. 471–480.
4.
Bataillon, Guillaume, Peter Naylor, Tatiana Popova, et al.. (2022). Deep learning identifies morphological patterns of homologous recombination deficiency in luminal breast cancers from whole slide images. Cell Reports Medicine. 3(12). 100872–100872. 33 indexed citations
5.
Naylor, Peter, Guillaume Bataillon, Marick Laé, et al.. (2022). Prediction of Treatment Response in Triple Negative Breast Cancer From Whole Slide Images. SHILAP Revista de lepidopterología. 2. 3 indexed citations
6.
Naylor, Peter, Joseph Boyd, Marick Laé, Fabien Reyal, & Thomas Walter. (2019). Predicting Residual Cancer Burden In A Triple Negative Breast Cancer Cohort. HAL (Le Centre pour la Communication Scientifique Directe). 933–937. 3 indexed citations
7.
Naylor, Peter, Marick Laé, Fabien Reyal, & Thomas Walter. (2018). Segmentation of Nuclei in Histopathology Images by deep regression of the distance map. HAL (Le Centre pour la Communication Scientifique Directe). 10 indexed citations
8.
Naylor, Peter, et al.. (2017). Nuclei segmentation in histopathology images using deep neural networks. 933–936. 131 indexed citations
9.
10.
Naylor, Peter, et al.. (2002). Unlocking the Potential from UKCS Low Deliverability Reservoirs. All Days. 1 indexed citations
11.
Naylor, Peter, et al.. (2001). Development Of In-situ Measurements To Determine Reservoir Condition Critical Gas Saturations During Depressurization. Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description. 42(4). 4 indexed citations
12.
Drummond, A. J., et al.. (2001). An Evaluation of Post-Waterflood Depressurisation of the South Brae Field, North Sea. SPE Annual Technical Conference and Exhibition. 18 indexed citations
13.
Naylor, Peter, et al.. (2001). Relative Permeability Measurements for Post-Waterflood Depressurization of the Miller Field, North Sea. SPE Reservoir Evaluation & Engineering. 4(4). 276–280. 5 indexed citations
14.
Naylor, Peter, et al.. (2000). Relative Permeability Measurements for Post-Waterflood Depressurisation of the Miller Field, North Sea. Proceedings of SPE Annual Technical Conference and Exhibition. 2 indexed citations
15.
Naylor, Peter, et al.. (2000). Relative Permeability Measurements for Post-Waterflood Depressurisation of the Miller Field, North Sea. SPE Annual Technical Conference and Exhibition. 21 indexed citations
16.
Naylor, Peter, et al.. (1996). Repeated ECS induces GluR1 mRNA but not NMDAR1A-G mRNA in the rat hippocampus. Molecular Brain Research. 35(1-2). 349–353. 35 indexed citations
17.
Naylor, Peter, et al.. (1996). Engineered depressurisation of waterflooded reservoirs. 1 indexed citations
18.
Naylor, Peter, et al.. (1996). Gravity drainage during gas injection. Petroleum Geoscience. 2(1). 69–74. 9 indexed citations
19.
Naylor, Peter, et al.. (1989). Further studies on head lice and their control in Tasmania.. PubMed. 18(3). 253–5. 4 indexed citations
20.
Naylor, Peter, et al.. (1989). Gravity-Stable Nitrogen Displacement of Oil. Proceedings of SPE Annual Technical Conference and Exhibition. 8 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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