N.M. Allinson

4.0k total citations
154 papers, 2.1k citations indexed

About

N.M. Allinson is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, N.M. Allinson has authored 154 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Computer Vision and Pattern Recognition, 42 papers in Artificial Intelligence and 31 papers in Electrical and Electronic Engineering. Recurrent topics in N.M. Allinson's work include Neural Networks and Applications (35 papers), CCD and CMOS Imaging Sensors (23 papers) and Particle Detector Development and Performance (19 papers). N.M. Allinson is often cited by papers focused on Neural Networks and Applications (35 papers), CCD and CMOS Imaging Sensors (23 papers) and Particle Detector Development and Performance (19 papers). N.M. Allinson collaborates with scholars based in United Kingdom, United States and South Africa. N.M. Allinson's co-authors include Hujun Yin, Jing Li, Xujiong Ye, Philip Evans, Tryphon Lambrou, Gavin Poludniowski, Mohammadreza Soltaninejad, Guang Yang, Franklyn A. Howe and Timothy L. Jones and has published in prestigious journals such as Analytical Chemistry, European Journal of Operational Research and International Journal of Radiation Oncology*Biology*Physics.

In The Last Decade

N.M. Allinson

141 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
N.M. Allinson United Kingdom 24 827 469 375 314 301 154 2.1k
Yongbing Zhang China 28 3.5k 4.2× 403 0.9× 292 0.8× 26 0.1× 28 0.1× 163 4.6k
Saeed Setayeshi Iran 22 200 0.2× 364 0.8× 200 0.5× 15 0.0× 46 0.2× 151 1.9k
Lin Wang China 32 819 1.0× 302 0.6× 144 0.4× 11 0.0× 127 0.4× 280 3.7k
Jiliu Zhou China 30 1.5k 1.9× 485 1.0× 273 0.7× 76 0.2× 143 0.5× 158 4.4k
Abdul Ahad S. Awwal United States 20 464 0.6× 451 1.0× 32 0.1× 42 0.1× 18 0.1× 138 2.4k
Michael J. Cree New Zealand 24 1.4k 1.6× 107 0.2× 84 0.2× 40 0.1× 48 0.2× 124 2.8k
M. Urban Czechia 12 3.0k 3.6× 242 0.5× 137 0.4× 11 0.0× 42 0.1× 60 3.8k
Jianmin Li China 24 1.1k 1.4× 368 0.8× 65 0.2× 10 0.0× 34 0.1× 103 1.8k
Alain Horé Canada 8 2.0k 2.4× 269 0.6× 46 0.1× 26 0.1× 24 0.1× 16 2.8k
Chandra Sekhar Seelamantula India 21 680 0.8× 157 0.3× 141 0.4× 11 0.0× 55 0.2× 168 1.7k

Countries citing papers authored by N.M. Allinson

Since Specialization
Citations

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

Fields of papers citing papers by N.M. Allinson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by N.M. Allinson. 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 N.M. Allinson. The network helps show where N.M. Allinson may publish in the future.

Co-authorship network of co-authors of N.M. Allinson

This figure shows the co-authorship network connecting the top 25 collaborators of N.M. Allinson. A scholar is included among the top collaborators of N.M. Allinson 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 N.M. Allinson. N.M. Allinson 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.
Winter, Alasdair, Adam Aitkenhead, N.M. Allinson, et al.. (2023). OPTIma: a tracking solution for proton computed tomography in high proton flux environments. Journal of Instrumentation. 18(4). P04026–P04026. 1 indexed citations
2.
Soltaninejad, Mohammadreza, Guang Yang, Tryphon Lambrou, et al.. (2018). Supervised learning based multimodal MRI brain tumour segmentation using texture features from supervoxels. Computer Methods and Programs in Biomedicine. 157. 69–84. 171 indexed citations
3.
Soltaninejad, Mohammadreza, Guang Yang, Tryphon Lambrou, et al.. (2016). Automated brain tumour detection and segmentation using superpixel-based extremely randomized trees in FLAIR MRI. International Journal of Computer Assisted Radiology and Surgery. 12(2). 183–203. 222 indexed citations
4.
Poludniowski, Gavin, T. Price, Chris Waltham, et al.. (2016). An experimental demonstration of a new type of proton computed tomography using a novel silicon tracking detector. Medical Physics. 43(11). 6129–6136. 15 indexed citations
5.
Zhang, Lei, Xujiong Ye, Tryphon Lambrou, et al.. (2016). A supervised texton based approach for automatic segmentation and measurement of the fetal head and femur in 2D ultrasound images. Physics in Medicine and Biology. 61(3). 1095–1115. 29 indexed citations
6.
Esposito, Michela, Philip Evans, S. Manolopoulos, et al.. (2015). CMOS Active Pixel Sensors as energy-range detectors for proton Computed Tomography. Journal of Instrumentation. 10(6). C06001–C06001. 11 indexed citations
7.
Poludniowski, Gavin, N.M. Allinson, & Philip Evans. (2015). Proton radiography and tomography with application to proton therapy. British Journal of Radiology. 88(1053). 20150134–20150134. 120 indexed citations
8.
Allport, P. P., G. Casse, N. A. Smith, et al.. (2015). Proton tracking for medical imaging and dosimetry. Journal of Instrumentation. 10(2). C02015–C02015. 18 indexed citations
9.
Soltaninejad, Mohammadreza, Tryphon Lambrou, Adnan N. Qureshi, N.M. Allinson, & Xujiong Ye. (2014). A hybrid method for haemorrhage segmentation in trauma brain CT. 99–104. 3 indexed citations
10.
Soltaninejad, Mohammadreza, Xujiong Ye, Guang Yang, N.M. Allinson, & Tryphon Lambrou. (2014). Brain Tumour Grading in Different MRI Protocols using SVM on Statistical Features.. Lincoln Repository (University of Lincoln). 259–264. 10 indexed citations
11.
Poludniowski, Gavin, N.M. Allinson, & Philip Evans. (2014). Proton computed tomography reconstruction using a backprojection-then-filtering approach. Physics in Medicine and Biology. 59(24). 7905–7918. 24 indexed citations
12.
Poludniowski, Gavin, N.M. Allinson, Michela Esposito, et al.. (2014). Proton-counting radiography for proton therapy: a proof of principle using CMOS APS technology. Physics in Medicine and Biology. 59(11). 2569–2581. 35 indexed citations
13.
Osmond, John, et al.. (2011). Imaging of moving fiducial markers during radiotherapy using a fast, efficient active pixel sensor based EPID. Medical Physics. 38(11). 6152–6159. 3 indexed citations
14.
Yin, Hujun, et al.. (2002). Image denoising using self-organizing map-based nonlinear independent component analysis. Neural Networks. 15(8-9). 1085–1098. 41 indexed citations
15.
Yin, Hujun & N.M. Allinson. (2001). Self-organizing mixture networks for probability density estimation. IEEE Transactions on Neural Networks. 12(2). 405–411. 77 indexed citations
16.
Kołcz, Aleksander & N.M. Allinson. (1999). Basis function models of the CMAC network. Neural Networks. 12(1). 107–126. 6 indexed citations
17.
Graham, Daniel B. & N.M. Allinson. (1999). Norm2-based face recognition. Figshare. 1 indexed citations
18.
Kołcz, Aleksander & N.M. Allinson. (1996). N-tuple Regression Network. Neural Networks. 9(5). 855–869. 14 indexed citations
19.
Allinson, N.M., et al.. (1994). FPGA acceleration of electronic design automation tasks. 337–344. 6 indexed citations
20.
Allinson, N.M., et al.. (1988). Digital Realisation of Self-Organising Maps. Neural Information Processing Systems. 1. 728–738. 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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