Blair Thornton

2.5k total citations
128 papers, 1.9k citations indexed

About

Blair Thornton is a scholar working on Ocean Engineering, Oceanography and Mechanics of Materials. According to data from OpenAlex, Blair Thornton has authored 128 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Ocean Engineering, 47 papers in Oceanography and 30 papers in Mechanics of Materials. Recurrent topics in Blair Thornton's work include Underwater Vehicles and Communication Systems (50 papers), Underwater Acoustics Research (40 papers) and Laser-induced spectroscopy and plasma (30 papers). Blair Thornton is often cited by papers focused on Underwater Vehicles and Communication Systems (50 papers), Underwater Acoustics Research (40 papers) and Laser-induced spectroscopy and plasma (30 papers). Blair Thornton collaborates with scholars based in Japan, United Kingdom and Australia. Blair Thornton's co-authors include Tomoko Takahashi, Tamaki Ura, Tetsuo Sakka, Adrian Bodenmann, Ayumu Matsumoto, Ayaka Tamura, Koichi Ohki, Takumi Sato, Y. Nosé and Tatsuo Nozaki and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Analytical Chemistry and Optics Express.

In The Last Decade

Blair Thornton

118 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Blair Thornton Japan 23 943 704 465 407 297 128 1.9k
Douglas P. Connelly United Kingdom 29 233 0.2× 73 0.1× 507 1.1× 241 0.6× 873 2.9× 52 2.9k
S. Musazzi Italy 11 350 0.4× 232 0.3× 102 0.2× 90 0.2× 27 0.1× 31 1.0k
Keith E. Livo United States 12 109 0.1× 216 0.3× 25 0.1× 55 0.1× 122 0.4× 58 2.6k
A. M. de Frutos Spain 30 119 0.1× 152 0.2× 12 0.0× 278 0.7× 90 0.3× 142 3.1k
Volker Dietrich Switzerland 22 101 0.1× 83 0.1× 51 0.1× 49 0.1× 37 0.1× 68 2.0k
Maurizio Migliaccio Italy 42 58 0.1× 18 0.0× 578 1.2× 397 1.0× 2.4k 8.1× 307 5.5k
Guoqiang Tang China 35 136 0.1× 60 0.1× 339 0.7× 14 0.0× 85 0.3× 140 5.3k
H. Edner Sweden 28 166 0.2× 122 0.2× 12 0.0× 590 1.4× 15 0.1× 80 2.2k
James C. Kinsey United States 21 46 0.0× 27 0.0× 823 1.8× 152 0.4× 531 1.8× 43 1.7k
Naomi Murdoch France 19 113 0.1× 40 0.1× 108 0.2× 17 0.0× 52 0.2× 79 1.3k

Countries citing papers authored by Blair Thornton

Since Specialization
Citations

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

Fields of papers citing papers by Blair Thornton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Blair Thornton

This figure shows the co-authorship network connecting the top 25 collaborators of Blair Thornton. A scholar is included among the top collaborators of Blair Thornton 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 Blair Thornton. Blair Thornton 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.
Massot‐Campos, Miquel, et al.. (2025). Self-supervised learning with multimodal remote sensed maps for seafloor visual class inference. The International Journal of Robotics Research. 44(14). 2340–2364. 1 indexed citations
2.
Massot‐Campos, Miquel, et al.. (2024). Leveraging Spatial Metadata in Machine Learning for Improved Objective Quantification of Geological Drill Core. Earth and Space Science. 11(3). 3 indexed citations
3.
Masoudi, Mojtaba, et al.. (2024). Optimizing Plankton Image Classification With Metadata-Enhanced Representation Learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17. 17117–17133. 1 indexed citations
4.
Matsumura, Tarojiro, Tomoko Takahashi, Kenji Nagata, et al.. (2024). High-Throughput Calibration-Free Laser-Induced Breakdown Spectroscopy. ACS Earth and Space Chemistry. 8(6). 1259–1271. 1 indexed citations
5.
Ura, Tamaki, et al.. (2024). Multirobot Multimodal Deep Sea Surveys: Use in Detailed Estimation of Manganese Crust Distribution. IEEE Robotics & Automation Magazine. 31(1). 84–95. 2 indexed citations
6.
Durden, Jennifer M., Brian J. Bett, Veerle A.I. Huvenne, et al.. (2024). Improving coral monitoring by reducing variability and bias in cover estimates from seabed images. Progress In Oceanography. 222. 103214–103214. 5 indexed citations
7.
Massot‐Campos, Miquel, et al.. (2023). Assessing benthic marine habitats colonized with posidonia oceanica using autonomous marine robots and deep learning: A Eurofleets campaign. Estuarine Coastal and Shelf Science. 291. 108438–108438. 2 indexed citations
8.
Pasqualino, Ilson, Menglan Duan, Zhuang Kang, et al.. (2022). Committee V.8: Subsea Technology. ePrints Soton (University of Southampton). 1 indexed citations
9.
Massot‐Campos, Miquel, et al.. (2022). Guiding Labelling Effort for Efficient Learning With Georeferenced Images. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(1). 593–607. 11 indexed citations
10.
Hall, Benjamin D., et al.. (2022). Development of a prototype autonomous inspection robot for offshore riser cables. Ocean Engineering. 257. 111485–111485. 12 indexed citations
11.
Prügel‐Bennett, Adam, et al.. (2022). GeoCLR: Georeference Contrastive Learning for Efficient Seafloor Image Interpretation. ePrints Soton (University of Southampton). 2. 1134–1155. 9 indexed citations
12.
Liu, Zonghua, Tomoko Takahashi, Dhugal J. Lindsay, et al.. (2021). Digital In-Line Holography for Large-Volume Analysis of Vertical Motion of Microscale Marine Plankton and Other Particles. IEEE Journal of Oceanic Engineering. 46(4). 1248–1260. 9 indexed citations
13.
Prügel‐Bennett, Adam, et al.. (2020). Learning features from georeferenced seafloor imagery with location guided autoencoders. Journal of Field Robotics. 38(1). 52–67. 33 indexed citations
14.
Banks, J., et al.. (2019). APPLICATIONS OF MOTION CAPTURE TECHNOLOGY IN A TOWING TANK. SPIRE - Sciences Po Institutional REpository. 1 indexed citations
15.
Thornton, Blair, et al.. (2019). Autonomous Landing of Underwater Vehicles Using High-Resolution Bathymetry. IEEE Journal of Oceanic Engineering. 45(4). 1252–1267. 10 indexed citations
16.
Thornton, Blair. (2019). Sizing Drop Weights for Deep Diving Submersibles Taking Into Account Nonuniform Seawater Density Profiles. IEEE Journal of Oceanic Engineering. 45(3). 979–989. 8 indexed citations
17.
Thornton, Blair, et al.. (2016). Support vector machine based classification of seafloor rock types measured underwater using Laser Induced Breakdown Spectroscopy. OCEANS 2016 - Shanghai. 1–4. 8 indexed citations
18.
Thornton, Blair, et al.. (2013). Positioning and control of an AUV inside a water pipeline for non-contact in-service inspection. ePrints Soton (University of Southampton). 1–10. 4 indexed citations
19.
Thornton, Blair, et al.. (2009). A conical laser light-sectioning method for navigation of Autonomous Underwater Vehicles for internal inspection of pipelines. ePrints Soton (University of Southampton). 1–9. 13 indexed citations
20.
Huang, Wuu-Liang, et al.. (2007). Dynamic Programming Approach to Image Segmentation and its Application to Pre-processing of Mammograms. 8(2). 51–56. 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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