P.J.G. Lisboa

731 total citations
35 papers, 532 citations indexed

About

P.J.G. Lisboa is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, P.J.G. Lisboa has authored 35 papers receiving a total of 532 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 9 papers in Control and Systems Engineering and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in P.J.G. Lisboa's work include Neural Networks and Applications (11 papers), Fault Detection and Control Systems (5 papers) and Blind Source Separation Techniques (4 papers). P.J.G. Lisboa is often cited by papers focused on Neural Networks and Applications (11 papers), Fault Detection and Control Systems (5 papers) and Blind Source Separation Techniques (4 papers). P.J.G. Lisboa collaborates with scholars based in United Kingdom, Italy and Belgium. P.J.G. Lisboa's co-authors include Stavros Perantonis, Wael El‐Deredy, C. Michael, Gareth‐Rhys Jones, P.C. Russell, Alfredo Vellido, K.J. Binns, Federico Ambrogi, Andrew R. Green and Daniele Soria and has published in prestigious journals such as Nuclear Physics B, Physics Letters B and Statistics in Medicine.

In The Last Decade

P.J.G. Lisboa

31 papers receiving 497 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
P.J.G. Lisboa United Kingdom	11	217	180	62	57	47	35	532
Kushal Kanti Ghosh India	17	462 2.1×	170 0.9×	34 0.5×	27 0.5×	48 1.0×	32	880
Zhiqiang Hu China	11	313 1.4×	161 0.9×	36 0.6×	24 0.4×	38 0.8×	52	785
Stéphane d’Ascoli France	5	282 1.3×	298 1.7×	13 0.2×	26 0.5×	54 1.1×	10	674
C. T. J. Dodson United Kingdom	16	48 0.2×	80 0.4×	22 0.4×	39 0.7×	31 0.7×	79	792
Michael Rudzsky Israel	15	175 0.8×	612 3.4×	23 0.4×	31 0.5×	36 0.8×	28	821
Shengyu Huang United States	13	53 0.2×	334 1.9×	65 1.0×	15 0.3×	19 0.4×	30	981
Zhou Xu China	21	300 1.4×	84 0.5×	16 0.3×	117 2.1×	45 1.0×	59	1.1k
Kerstin Bunte Netherlands	14	300 1.4×	309 1.7×	25 0.4×	44 0.8×	26 0.6×	76	767
J. Gil Israel	10	205 0.9×	386 2.1×	13 0.2×	49 0.9×	34 0.7×	20	769

Countries citing papers authored by P.J.G. Lisboa

Since Specialization

Citations

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

Fields of papers citing papers by P.J.G. Lisboa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by P.J.G. Lisboa. 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 P.J.G. Lisboa. The network helps show where P.J.G. Lisboa may publish in the future.

Co-authorship network of co-authors of P.J.G. Lisboa

This figure shows the co-authorship network connecting the top 25 collaborators of P.J.G. Lisboa. A scholar is included among the top collaborators of P.J.G. Lisboa 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 P.J.G. Lisboa. P.J.G. Lisboa 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

Biganzoli, Elia, Danila Coradini, Federico Ambrogi, et al.. (2011). p53 Status Identifies Two Subgroups of Triple-negative Breast Cancers with Distinct Biological Features. Japanese Journal of Clinical Oncology. 41(2). 172–179. 48 indexed citations

Garibaldi, Jonathan M., Daniele Soria, Federico Ambrogi, et al.. (2008). Identification of key breast cancer phenotypes. European Journal of Cancer Supplements. 6(7). 183–183. 2 indexed citations

Fisher, Anthony C., Wael El‐Deredy, Richard Hagan, Malcolm C. Brown, & P.J.G. Lisboa. (2006). Removal of eye movement artefacts from single channel recordings of retinal evoked potentials using synchronous dynamical embedding and independent component analysis. Medical & Biological Engineering & Computing. 45(1). 69–77. 4 indexed citations

Lisboa, P.J.G., et al.. (2005). The Interpretation Of Supervised Neural Networks. 2. 11–17. 4 indexed citations

Vellido, Alfredo, Wael El‐Deredy, & P.J.G. Lisboa. (2003). Selective smoothing of the generative topographic mapping. IEEE Transactions on Neural Networks. 14(4). 847–852. 23 indexed citations

Lisboa, P.J.G., et al.. (2002). Tumour grading from magnetic resonance spectroscopy: a comparison of feature extraction with variable selection. Statistics in Medicine. 22(1). 147–164. 54 indexed citations

Branston, Neil M., Wael El‐Deredy, P.J.G. Lisboa, & D.G.T. Thomas. (2002). Visualisation of human basal ganglia neuron responses using the generative topographic mapping (GTM) algorithm. 1. 326–331.

Lisboa, P.J.G., et al.. (1999). An Implementation of the Hough Transformation for the Identification and Labelling of Fixed Period Sinusoidal Curves. Computer Vision and Image Understanding. 74(1). 96–100. 39 indexed citations

Ahmed, Shamim, P.C. Russell, P.J.G. Lisboa, & Gareth‐Rhys Jones. (1997). Parameter monitoring using neural-network-processedchromaticity. IEE Proceedings - Science Measurement and Technology. 144(6). 257–262. 2 indexed citations

10.

Kodogiannis, Vassilis, P.J.G. Lisboa, & J. Lucas. (1994). Long Range Predictive Controller for Underwater Robotic Vehicles using Recurrent Neural Networks. WestminsterResearch (University of Westminster). 3 indexed citations

11.

Kodogiannis, Vassilis, P.J.G. Lisboa, & J. Lucas. (1994). Neural network based predictive control systems for underwater robotic vehicles. WestminsterResearch (University of Westminster). 369–376. 4 indexed citations

12.

Gomm, J.B., et al.. (1994). Accurate multi-step-ahead prediction of non-linear systems using the MLP neural network with spread encoding. Transactions of the Institute of Measurement and Control. 16(4). 203–213. 7 indexed citations

13.

Perantonis, Stavros & P.J.G. Lisboa. (1992). Translation, rotation, and scale invariant pattern recognition by high-order neural networks and moment classifiers. IEEE Transactions on Neural Networks. 3(2). 241–251. 171 indexed citations

14.

Binns, K.J., et al.. (1992). Use of canned rotors in high-field permanent magnet machines. IEE Proceedings B Electric Power Applications. 139(5). 471–471. 11 indexed citations

15.

Lisboa, P.J.G. & Stavros Perantonis. (1991). Invariant digit recognition by Zernike moments and third-order neural networks. 82–85. 4 indexed citations

16.

Lisboa, P.J.G.. (1991). Neural networks in vision. 1 indexed citations

17.

Lisboa, P.J.G. & Stavros Perantonis. (1991). Complete solution of the local minima in the XOR problem. Network Computation in Neural Systems. 2(1). 119–124. 27 indexed citations

18.

Lisboa, P.J.G. & Stavros Perantonis. (1991). Complete solution of the local minima in the XOR problem. Network Computation in Neural Systems. 2(1). 119–124. 17 indexed citations

19.

Lisboa, P.J.G. & C. Michael. (1982). Lattices in group manifolds: Applications to lattice gauge theory. Nuclear Physics B. 210(1). 15–28. 12 indexed citations

20.

Lisboa, P.J.G. & C. Michael. (1982). Discrete subsets of SU(3) for lattice gauge theory. Physics Letters B. 113(4). 303–304. 23 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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