Michael Firman

1.4k total citations
12 papers, 365 citations indexed

About

Michael Firman is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Michael Firman has authored 12 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 3 papers in Aerospace Engineering. Recurrent topics in Michael Firman's work include Advanced Vision and Imaging (4 papers), Robotics and Sensor-Based Localization (3 papers) and Advanced Neural Network Applications (3 papers). Michael Firman is often cited by papers focused on Advanced Vision and Imaging (4 papers), Robotics and Sensor-Based Localization (3 papers) and Advanced Neural Network Applications (3 papers). Michael Firman collaborates with scholars based in United Kingdom, United States and Australia. Michael Firman's co-authors include Gabriel Brostow, Oisin Mac Aodha, Simon Julier, Kate E. Jones, Alison Fairbrass, Carol Williams, Helena Titheridge, Stuart Parsons, Farkas Szodoray‐Parádi and Robin Freeman and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS Computational Biology and Methods in Ecology and Evolution.

In The Last Decade

Michael Firman

12 papers receiving 349 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael Firman United Kingdom	7	138	117	100	58	51	12	365
László Czúni Hungary	11	126 0.9×	19 0.2×	50 0.5×	47 0.8×	44 0.9×	52	363
Thomas Huang United States	9	473 3.4×	8 0.1×	78 0.8×	42 0.7×	8 0.2×	15	640
Eraldo Ribeiro United States	12	205 1.5×	19 0.2×	24 0.2×	26 0.4×	13 0.3×	48	424
Cheng‐Ming Huang Taiwan	10	194 1.4×	43 0.4×	106 1.1×	10 0.2×	82 1.6×	63	482
Rafael Álvarez Spain	7	55 0.4×	222 1.9×	167 1.7×	94 1.6×	73 1.4×	30	401
Jau-Ling Shih Taiwan	10	453 3.3×	50 0.4×	16 0.2×	170 2.9×	8 0.2×	32	585
Sara Beery United States	7	88 0.6×	50 0.4×	191 1.9×	19 0.3×	54 1.1×	18	471
Kim Arild Steen Denmark	9	115 0.8×	17 0.1×	118 1.2×	27 0.5×	11 0.2×	20	462
Roland J. Arsenault United States	7	114 0.8×	61 0.5×	127 1.3×	26 0.4×	11 0.2×	21	378
Mark D. Skowronski United States	15	37 0.3×	170 1.5×	135 1.4×	239 4.1×	165 3.2×	42	874

Countries citing papers authored by Michael Firman

Since Specialization

Citations

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

Fields of papers citing papers by Michael Firman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Firman

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

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

1.

Watson, J.S., et al.. (2024). AirPlanes: Accurate Plane Estimation via 3D-Consistent Embeddings. 5270–5280. 1 indexed citations

2.

Garcia-Hernando, Guillermo, Áron Monszpart, Marc Pollefeys, et al.. (2023). Removing Objects From Neural Radiance Fields. 16528–16538. 27 indexed citations

3.

Watson, J.S., Sara Vicente, Oisin Mac Aodha, et al.. (2023). Heightfields for Efficient Scene Reconstruction for AR. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 5839–5849. 3 indexed citations

4.

Watson, J.S., et al.. (2023). Virtual Occlusions Through Implicit Depth. 9053–9064. 3 indexed citations

5.

Firman, Michael, et al.. (2021). Panoptic Segmentation Forecasting. 2279–2288. 5 indexed citations

6.

Gallacher, Sarah, Duncan Wilson, Alison Fairbrass, et al.. (2021). Shazam for bats: Internet of Things for continuous real‐time biodiversity monitoring. SHILAP Revista de lepidopterología. 3(3). 171–183. 14 indexed citations

7.

Fairbrass, Alison, Michael Firman, Carol Williams, et al.. (2018). CityNet—Deep learning tools for urban ecoacoustic assessment. Methods in Ecology and Evolution. 10(2). 186–197. 52 indexed citations

8.

Aodha, Oisin Mac, Rory Gibb, Kate E. Barlow, et al.. (2018). Bat detective—Deep learning tools for bat acoustic signal detection. PLoS Computational Biology. 14(3). e1005995–e1005995. 140 indexed citations

9.

Firman, Michael, Neill D. F. Campbell, Lourdes Agapito, & Gabriel Brostow. (2018). DiverseNet: When One Right Answer is not Enough. 5598–5607. 13 indexed citations

10.

Firman, Michael, et al.. (2018). RecurBot. 1–6. 3 indexed citations

11.

Firman, Michael, Oisin Mac Aodha, Simon Julier, & Gabriel Brostow. (2016). Structured Prediction of Unobserved Voxels from a Single Depth Image. 5431–5440. 98 indexed citations

12.

Firman, Michael, Diego Thomas, Simon Julier, & Akihiro Sugimoto. (2013). Learning to discover objects in RGB-D images using correlation clustering. 233. 1107–1112. 6 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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