A. Marrs

415 citations
22 papers · 317 indexed · h-index 10

Impact in

Papers in

A. Marrs

21 papers receiving 290 citations

Peers

A. Marrs
Comparison fields: 5 of 45
  • Artificial Intelligence 259
  • Computer Networks and Communications 144
  • Aerospace Engineering 90
  • Control and Systems Engineering 79
  • Signal Processing 22
Replace Hans Driessen with:
Hans Driessen Netherlands
Xiangdong Lin United States
H. Driessen Netherlands
R. Streit United States
X.R. Li United States
Sangjin Hong United States
E.A. Bloem Netherlands
Felix Govaers Germany
J.A. Roecker United States
Feng Lian China
A. Marrs relative to Hans Driessen Netherlands Hans Driessen's profile →
Citations per field
00.5×1.5×
Hans Driessen · 1×
Citations per year

Countries citing papers authored by A. Marrs

Since Specialization
Citations

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

Fields of papers citing papers by A. Marrs

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 20 scholars most cited alongside A. Marrs, 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 A. Marrs Line = papers co-authored together A. Marrs links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20098
2 200837
3 20056
4 20056
5 200558
6 20042
7 200419
8 20041
9 200319
10 200312
11 200347
12 20025
13 200214
14 200220
15
Incorporation of out-of-sequence measurements in non-linear dynamic systems using particle filters
20024
16 20013
17 20002
18 19991
19
An Application of Reversible-Jump MCMC to Multivariate Spherical Gaussian Mixtures
199712
20 19972

About A. Marrs

A. Marrs is a scholar working on Artificial Intelligence, Control and Systems Engineering, Computer Networks and Communications, Oceanography and Surfaces, Coatings and Films, having authored 22 papers that have together received 317 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (16 papers), Fault Detection and Control Systems (5 papers), Distributed Sensor Networks and Detection Algorithms (5 papers), Bayesian Methods and Mixture Models (3 papers), Underwater Acoustics Research (2 papers), Gaussian Processes and Bayesian Inference (2 papers), Thin-Film Transistor Technologies (2 papers) and Inertial Sensor and Navigation (2 papers). The work is most often cited by research in Artificial Intelligence (259 citations), Computer Networks and Communications (144 citations), Aerospace Engineering (90 citations), Control and Systems Engineering (79 citations) and Signal Processing (22 citations). A. Marrs has collaborated with scholars based in United Kingdom, United States and France. Frequent co-authors include Matthew Orton, Simon Maskell, Peter Willett, Marcel L. Hernandez, Neil Gordon, Mahendra Mallick, F. Palmieri, Stefano Maranò, Randal Douc and Yaakov Bar‐Shalom. Their work appears in journals such as IEEE Transactions on Aerospace and Electronic Systems, Journal of Crystal Growth, Image and Vision Computing, Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences and IEEE Transactions on Signal Processing.

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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