John Mullane

721 citations
15 papers · 547 indexed · h-index 11

Impact in

Papers in

John Mullane

15 papers receiving 521 citations

Peers

John Mullane
Comparison fields: 5 of 39
  • Aerospace Engineering 381
  • Artificial Intelligence 338
  • Ocean Engineering 86
  • Instrumentation 19
  • Computational Mathematics 3
Replace Hatem Hmam with:
Hatem Hmam Australia
Gongjian Zhou China
Tisheng Zhang China
Nikolas Trawny United States
Donka Angelova Bulgaria
Jonas Callmer Sweden
Xiwei Bai Hong Kong
Jizhou Lai China
Shengyu Li China
Xiaolin Gong China
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Citations per field
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Citations per year

Countries citing papers authored by John Mullane

Since Specialization
Citations

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

Fields of papers citing papers by John Mullane

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 11 scholars most cited alongside John Mullane, 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 John Mullane Line = papers co-authored together John Mullane links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 201463
2 20135
3 20132
4
Robotic Navigation and Mapping with Radar
201249
5 2011214
6 20118
7 201146
8
Random Finite Sets for Robot Mapping & SLAM: New Concepts in Autonomous Robotic Map Representations
20115
9 201013
10 201029
11 201036
12 200917
13 200830
14 200615
15 200615

About John Mullane

John Mullane is a scholar working on Aerospace Engineering, Artificial Intelligence, Ocean Engineering, Oceanography and Electrical and Electronic Engineering, having authored 15 papers that have together received 547 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (11 papers), Robotics and Sensor-Based Localization (10 papers), Indoor and Outdoor Localization Technologies (7 papers), Underwater Vehicles and Communication Systems (3 papers), Underwater Acoustics Research (2 papers), Advanced Image and Video Retrieval Techniques (1 paper), Distributed Sensor Networks and Detection Algorithms (1 paper) and Remote Sensing and LiDAR Applications (1 paper). The work is most often cited by research in Aerospace Engineering (381 citations), Artificial Intelligence (338 citations), Ocean Engineering (86 citations), Instrumentation (19 citations) and Computational Mathematics (3 citations). John Mullane has collaborated with scholars based in Singapore, Australia and Chile. Frequent co-authors include Martin Adams, Ba‐Ngu Vo, Ba-Tuong Vo, W.S. Wijesoma, Ronald Mahler, Nicholas M. Patrikalakis, Matthew Adams, Martin R. Adams, A.C. Rao and Franz S. Hover. Their work appears in journals such as Robotics and Autonomous Systems, IEEE Intelligent Transportation Systems Magazine, IEEE Sensors Journal, IEEE Transactions on Robotics and IEEE Robotics & Automation Magazine.

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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