David Connah

734 total citations
30 papers, 483 citations indexed

About

David Connah is a scholar working on Computer Vision and Pattern Recognition, Atomic and Molecular Physics, and Optics and Media Technology. According to data from OpenAlex, David Connah has authored 30 papers receiving a total of 483 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computer Vision and Pattern Recognition, 15 papers in Atomic and Molecular Physics, and Optics and 6 papers in Media Technology. Recurrent topics in David Connah's work include Color Science and Applications (15 papers), Image Enhancement Techniques (10 papers) and Image and Signal Denoising Methods (3 papers). David Connah is often cited by papers focused on Color Science and Applications (15 papers), Image Enhancement Techniques (10 papers) and Image and Signal Denoising Methods (3 papers). David Connah collaborates with scholars based in United Kingdom, Finland and Canada. David Connah's co-authors include Stephen Westland, Vien Cheung, Jon Yngve Hardeberg, Changjun Li, Caterina Ripamonti, Mitchell G. A. Thomson, Graham D. Finlayson, Hassan Ugail, Marcelo Bertalmı́o and Mark S. Drew and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Image Processing and Optics Express.

In The Last Decade

David Connah

29 papers receiving 434 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
David Connah United Kingdom	11	282	256	109	49	46	30	483
Michael Stokes United States	4	195 0.7×	272 1.1×	68 0.6×	31 0.6×	61 1.3×	9	441
Di-Yuan Tzeng United States	7	257 0.9×	144 0.6×	67 0.6×	19 0.4×	87 1.9×	9	342
Steven D. Hordley United Kingdom	9	413 1.5×	517 2.0×	128 1.2×	21 0.4×	93 2.0×	17	630
Marco Buzzelli Italy	10	64 0.2×	303 1.2×	99 0.9×	39 0.8×	24 0.5×	49	525
Vladimir Vezhnevets Tajikistan	7	72 0.3×	599 2.3×	60 0.6×	44 0.9×	19 0.4×	11	761
Chang‐Hwan Son South Korea	12	144 0.5×	376 1.5×	189 1.7×	50 1.0×	21 0.5×	72	515
Antony Lam Japan	12	60 0.2×	291 1.1×	231 2.1×	172 3.5×	18 0.4×	23	529
Jean-Christophe Terrillon Japan	6	55 0.2×	410 1.6×	48 0.4×	20 0.4×	16 0.3×	14	507
Mahmoud Afifi Canada	10	113 0.4×	329 1.3×	101 0.9×	25 0.5×	24 0.5×	24	449
Seoung Wug Oh United States	13	70 0.2×	982 3.8×	246 2.3×	28 0.6×	12 0.3×	22	1.1k

Countries citing papers authored by David Connah

Since Specialization

Citations

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

Fields of papers citing papers by David Connah

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Connah

This figure shows the co-authorship network connecting the top 25 collaborators of David Connah. A scholar is included among the top collaborators of David Connah 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 David Connah. David Connah 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:

20 of 20 papers shown

Cooper, Patricia A., et al.. (2017). A Non-invasive 2D Digital Imaging Method for Detection of Surface Lesions Using Machine Learning. Bradford Scholars (University of Bradford). 166–169. 1 indexed citations

Xiao, Kaida, et al.. (2016). Improved method for skin reflectance reconstruction from camera images. Optics Express. 24(13). 14934–14934. 43 indexed citations

Ugail, Hassan, et al.. (2016). Automatic age and gender classification using supervised appearance model. Journal of Electronic Imaging. 25(6). 61605–61605. 18 indexed citations

Ugail, Hassan, et al.. (2016). The Bradford Multi-Modal Gait Database: Gateway to Using Static Measurements to Create a Dynamic Gait Signature. British Journal of Applied Science & Technology. 14(1). 1–10. 4 indexed citations

Finlayson, Graham D., et al.. (2016). Estimating individual cone fundamentals from their color-matching functions. Journal of the Optical Society of America A. 33(8). 1579–1579. 4 indexed citations

Connah, David, Hassan Ugail, Patricia A. Cooper, et al.. (2016). The use of thermographic imaging to evaluate therapeutic response in human tumour xenograft models. Scientific Reports. 6(1). 7 indexed citations

Connah, David, et al.. (2016). Weighted Constrained Hue-Plane Preserving Camera Characterization. IEEE Transactions on Image Processing. 25(9). 4329–4339. 8 indexed citations

Connah, David, Mark S. Drew, & Graham D. Finlayson. (2015). Spectral edge: gradient-preserving spectral mapping for image fusion. Journal of the Optical Society of America A. 32(12). 2384–2384. 7 indexed citations

Vázquez-Corral, Javier, David Connah, & Marcelo Bertalmı́o. (2014). Perceptual Color Characterization of Cameras. Sensors. 14(12). 23205–23229. 23 indexed citations

10.

Finlayson, Graham D., David Connah, & Mark S. Drew. (2011). Lookup-Table-Based Gradient Field Reconstruction. IEEE Transactions on Image Processing. 20(10). 2827–2836. 12 indexed citations

11.

Connah, David, Graham D. Finlayson, & Marina Bloj. (2007). Seeing Beyond Luminance: A Psychophysical Comparison of Techniques for Converting Colour Images to Greyscale. Color and Imaging Conference. 15(1). 336–341. 8 indexed citations

12.

Connah, David & Graham D. Finlayson. (2006). Using Local Binary Pattern Operators for Colour Constant Image Indexing. Conference on Colour in Graphics Imaging and Vision. 3(1). 60–64. 9 indexed citations

13.

Cheung, Vien, Changjun Li, Jon Yngve Hardeberg, David Connah, & Stephen Westland. (2005). Characterization of trichromatic color cameras by using a new multispectral imaging technique. Journal of the Optical Society of America A. 22(7). 1231–1231. 80 indexed citations

14.

Cheung, Vien, Stephen Westland, David Connah, & Caterina Ripamonti. (2004). A comparative study of the characterisation of colour cameras by means of neural networks and polynomial transforms. Coloration Technology. 120(1). 19–25. 93 indexed citations

15.

Connah, David, Stephen Westland, & Mitchell G. A. Thomson. (2002). Optimization of a Multispectral Imaging System. Conference on Colour in Graphics Imaging and Vision. 1(1). 619–622. 6 indexed citations

16.

Connah, David, Stephen Westland, & Mitchell G. A. Thomson. (2002). Parametric investigation of multispectral imaging. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 4421. 943–943. 1 indexed citations

17.

Connah, David, et al.. (1997). Virtual actors that can perform scripts and improvise roles. 317–322. 9 indexed citations

18.

Connah, David, et al.. (1988). A Testbed for Research on Cooperating Agents.. European Conference on Artificial Intelligence. 20(3). 445–447.

19.

Connah, David, et al.. (1988). Onbeing there: why simulated reality is better than the real thing. Artificial Intelligence Review. 2(3). 143–150. 1 indexed citations

20.

Connah, David, et al.. (1983). Segmentation by colour. Radio and Electronic Engineer. 53(4). 153–153. 2 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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