Jen Jen Chung

49 papers receiving 707 citations

Hit Papers

Proceedings of the 18th International Conference on Auton...2019202620212023201950100150200250

Peers

Jen Jen Chung
Comparison fields: 5 of 88
  • Artificial Intelligence 294
  • Computer Vision and Pattern Recognition 237
  • Aerospace Engineering 201
  • Control and Systems Engineering 118
  • Computer Networks and Communications 92
Replace Antonio Berlanga with:
Antonio Berlanga Spain
Jincai Huang China
Guan Yuan China
Yara Rizk Lebanon
Dushyant Rao India
Raj Madhavan United States
Hanan Abdullah Mengash Saudi Arabia
John Wang United States
Alexander Aved United States
Junfei Qiu China
Jen Jen Chung relative to Antonio Berlanga Spain Antonio Berlanga's profile →
Citations per field
00.5×4.5×
Antonio Berlanga · 1×
Citations per year

Countries citing papers authored by Jen Jen Chung

Since Specialization
Citations

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

Fields of papers citing papers by Jen Jen Chung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jen Jen Chung

This figure shows the co-authorship network connecting the top 25 collaborators of Jen Jen Chung. A scholar is included among the top collaborators of Jen Jen Chung 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 Jen Jen Chung. Jen Jen Chung 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
#WorkIndexed citations
1 0
2 0
3 11
4 0
5 0
6 2
7 8
8 6
9 9
10 4
11 36
12 5
13
Fast and Accurate Mapping for Autonomous Racing.
2
14
MultiPoint: Cross-spectral registration of thermal and optical aerial imagery.
4
15
Informative Path Planning and Mapping for Active Sensing Under Localization Uncertainty.
3
16
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systemsbreakdown →
274
17 13
18 3
19 12
20 27

About Jen Jen Chung

Jen Jen Chung is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Artificial Intelligence, having authored 54 papers that have together received 734 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (15 papers), Robotic Path Planning Algorithms (14 papers) and Reinforcement Learning in Robotics (13 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (237 citations), Artificial Intelligence (294 citations) and Aerospace Engineering (201 citations). Jen Jen Chung has collaborated with scholars based in Switzerland, Australia and United States. Frequent co-authors include Roland Siegwart, Kagan Tumer, Lorenzo Sabattini, Damjan Miklić, Nicholas R. J. Lawrance, Juan Nieto, Teresa Vidal‐Calleja, Marija Popović, Gregory Hitz and Inkyu Sa. Their work appears in journals such as Nature Communications, The International Journal of Robotics Research and IEEE Transactions on Intelligent Transportation Systems.

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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