Phil Legg

1.6k citations
57 papers · 1.0k indexed · h-index 17

Impact in

Papers in

Phil Legg

54 papers receiving 966 citations

Peers

Phil Legg
Comparison fields: 5 of 111
  • Signal Processing 268
  • Computer Networks and Communications 380
  • Information Systems 358
  • Computer Vision and Pattern Recognition 281
  • Artificial Intelligence 257
Replace Giorgos Stamou with:
Giorgos Stamou Greece
Ankita Jain India
Abhinav Kumar India
Dong Hyun Jeong United States
Federico Álvarez Spain
Chao Yang China
Mingyu Chen China
Josep Lluís Arcos Spain
Ji Ming United Kingdom
Sajid Nazir United Kingdom
Phil Legg relative to Giorgos Stamou Greece Giorgos Stamou's profile →
Citations per field
00.5×3.5×
Giorgos Stamou · 1×
Citations per year

Countries citing papers authored by Phil Legg

Since Specialization
Citations

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

Fields of papers citing papers by Phil Legg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Phil Legg, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Phil Legg Line = papers co-authored together Phil Legg links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20251
4 20242
5 20235
6 20231
7 20230
8 20222
9 202133
10 201534
11 201591
12 20143
13 201347
14 201323
15 201354
16 20136
17 201130
18 20113
19 20117
20 200912

About Phil Legg

Phil Legg is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Computer Science Applications, Computer Graphics and Computer-Aided Design and Computer Networks and Communications, having authored 57 papers that have together received 1.0k indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (16 papers), Data Visualization and Analytics (14 papers), Advanced Malware Detection Techniques (12 papers), Information and Cyber Security (9 papers), Video Analysis and Summarization (6 papers), Anomaly Detection Techniques and Applications (6 papers), Medical Image Segmentation Techniques (5 papers) and Adversarial Robustness in Machine Learning (5 papers). The work is most often cited by research in Signal Processing (268 citations), Computer Networks and Communications (380 citations), Information Systems (358 citations), Computer Vision and Pattern Recognition (281 citations) and Artificial Intelligence (257 citations). Phil Legg has collaborated with scholars based in United Kingdom, United States and China. Frequent co-authors include Michael Goldsmith, Sadie Creese, Oliver Buckley, I.W. Griffiths, Jason R. C. Nurse, Paul L. Rosin, James P. Morgan, David Chung, Gordon Wright and Monica T. Whitty. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, IEEE Systems Journal, Human-centric Computing and Information Sciences, Computers & Security and IEEE Computer Graphics and Applications.

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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