Philip Moore

4.3k total citations
170 papers, 2.7k citations indexed

About

Philip Moore is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Philip Moore has authored 170 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Computer Vision and Pattern Recognition, 31 papers in Artificial Intelligence and 29 papers in Computer Networks and Communications. Recurrent topics in Philip Moore's work include Context-Aware Activity Recognition Systems (35 papers), Manufacturing Process and Optimization (16 papers) and EEG and Brain-Computer Interfaces (15 papers). Philip Moore is often cited by papers focused on Context-Aware Activity Recognition Systems (35 papers), Manufacturing Process and Optimization (16 papers) and EEG and Brain-Computer Interfaces (15 papers). Philip Moore collaborates with scholars based in United Kingdom, China and Sweden. Philip Moore's co-authors include Bin Hu, Junsheng Pu, Lihui Wang, Göran Adamson, Magnus Holm, Jihong Wang, Xiaowei Zhang, Xiaoyu Yang, Hai Van Pham and Amos H.C. Ng and has published in prestigious journals such as SHILAP Revista de lepidopterología, European Journal of Operational Research and Sensors.

In The Last Decade

Philip Moore

160 papers receiving 2.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Philip Moore United Kingdom 27 506 484 395 389 317 170 2.7k
Yingzi Lin United States 29 501 1.0× 400 0.8× 390 1.0× 307 0.8× 642 2.0× 128 3.4k
Rubén Morales-Menéndez Mexico 32 504 1.0× 320 0.7× 986 2.5× 358 0.9× 511 1.6× 195 4.4k
Chris Baber United Kingdom 36 122 0.2× 390 0.8× 537 1.4× 622 1.6× 353 1.1× 239 5.1k
David Kaber United States 36 247 0.5× 724 1.5× 503 1.3× 343 0.9× 523 1.6× 206 6.0k
Sabina Jeschke Germany 18 427 0.8× 127 0.3× 244 0.6× 145 0.4× 361 1.1× 228 2.0k
Mary Lou Maher United States 33 428 0.8× 185 0.4× 959 2.4× 299 0.8× 131 0.4× 209 3.5k
Barbara Hayes‐Roth United States 27 390 0.8× 477 1.0× 2.0k 5.0× 549 1.4× 507 1.6× 108 5.0k
Jessie Y. C. Chen United States 25 119 0.2× 443 0.9× 1.0k 2.6× 344 0.9× 496 1.6× 79 4.4k
Yuansong Qiao Ireland 20 677 1.3× 106 0.2× 166 0.4× 446 1.1× 133 0.4× 125 2.3k
Andry Rakotonirainy Australia 34 92 0.2× 223 0.5× 287 0.7× 422 1.1× 317 1.0× 237 3.7k

Countries citing papers authored by Philip Moore

Since Specialization
Citations

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

Fields of papers citing papers by Philip Moore

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Philip Moore

This figure shows the co-authorship network connecting the top 25 collaborators of Philip Moore. A scholar is included among the top collaborators of Philip Moore 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 Philip Moore. Philip Moore 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.
Moore, Philip, et al.. (2024). A Generative Artificial Intelligence Using Multilingual Large Language Models for ChatGPT Applications. Applied Sciences. 14(7). 3036–3036. 12 indexed citations
2.
Pham, Hai Van, et al.. (2024). Proposed Multi-ST Model for Collaborating Multiple Robots in Dynamic Environments. Machines. 12(11). 797–797. 2 indexed citations
3.
Moore, Philip, et al.. (2024). Determination of Airborne Release Fractions from Loose Powder Contamination Under Impact Stress. Nuclear Technology. 211(3). 598–606.
4.
Moore, Philip, et al.. (2022). An exploration of staff experience and participation in a perinatal and infant mental health network group. Irish Journal of Psychological Medicine. 40(4). 554–560.
5.
Pham, Hai Van, et al.. (2021). Hierarchical Pooling in Graph Neural Networks to Enhance Classification Performance in Large Datasets. Lanzhou University Institutional Repository. 17 indexed citations
6.
Pham, Hai Van, et al.. (2021). Hierarchical Pooling in Graph Neural Networks to Enhance Classification Performance in Large Datasets. Sensors. 21(18). 6070–6070. 1 indexed citations
7.
Yan, Xiu-Tian, David Bradley, & Philip Moore. (2018). Reinventing Mechatronics : Proceedings of Mechatronics 2018. 1 indexed citations
8.
Chen, Jing, Bin Hu, Yue Wang, et al.. (2017). Subject-independent emotion recognition based on physiological signals: a three-stage decision method. BMC Medical Informatics and Decision Making. 17(S3). 167–167. 26 indexed citations
9.
Hu, Bin, Yun Su, Philip Moore, et al.. (2016). Feature Selection for Optimized High-Dimensional Biomedical Data Using an Improved Shuffled Frog Leaping Algorithm. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 15(6). 1765–1773. 78 indexed citations
10.
Liu, Hong, Bin Hu, & Philip Moore. (2015). HCI Model with Learning Mechanism for Cooperative Design in Pervasive Computing Environment. 網際網路技術學刊. 16(2). 201–210. 5 indexed citations
11.
Moore, Philip & Hai Van Pham. (2015). Personalization and rule strategies in data-intensive intelligent context-aware systems. The Knowledge Engineering Review. 30(2). 140–156. 14 indexed citations
12.
Yao, Zhijun, et al.. (2015). A review of structural and functional brain networks: small world and atlas. Brain Informatics. 2(1). 45–52. 57 indexed citations
13.
Zhang, Xiaowei, et al.. (2014). Ontology driven decision support for the diagnosis of mild cognitive impairment. Computer Methods and Programs in Biomedicine. 113(3). 781–791. 32 indexed citations
14.
Fortiş, Teodor-Florin, et al.. (2014). Applying the Prometheus Methodology for an Internet of Things Architecture. Lanzhou University Institutional Repository. 435–442. 9 indexed citations
15.
Adamson, Göran, Lihui Wang, Magnus Holm, & Philip Moore. (2014). Function Block Approach for Adaptive Robotic Control in Virtual and Real Environments. 473–479. 2 indexed citations
16.
Moore, Philip, Tarik Qassem, & Fatos Xhafa. (2014). 'NoSQL' and Electronic Patient Record Systems: Opportunities and Challenges. UPCommons institutional repository (Universitat Politècnica de Catalunya). 1. 300–307. 7 indexed citations
17.
Moore, Philip, Magnus Holm, Göran Adamson, & Lihui Wang. (2012). An IEC 61499 Function Block based Approach for CNC Machining Operations. Falmouth University Research Repository (FURR) (Falmouth University). 1. 115–121. 3 indexed citations
18.
Adamson, Göran, Magnus Holm, Lihui Wang, & Philip Moore. (2012). Adaptive Assembly Feature Based Function Block Control of Robotic Assembly Operations. 1. 8–13. 2 indexed citations
19.
Moore, Philip, et al.. (2011). Medicines Reconciliation Using a Shared Electronic Health Care Record. Journal of Patient Safety. 7(3). 148–154. 22 indexed citations
20.
Molineaux, Matthew, David W. Aha, & Philip Moore. (2008). Learning Continuous Action Models in a Real-Time Strategy Environment. The Florida AI Research Society. 257–262. 15 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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