Su Pang

808 citations
15 papers · 498 · 1 hit paper · h-index 7

Impact in

Papers in

Su Pang

14 papers receiving 493 citations

Su Pang's Hit Papers

CLOCs: Camera-LiDAR Object Candidates Fusion for 3D Object Detection 2020 · 323 citations
3230+2+4Years since publication100200300

Peers

Su Pang
Comparison fields: 5 of 59
  • Computer Vision and Pattern Recognition 364
  • Instrumentation 46
  • Aerospace Engineering 246
  • Geology 53
  • Automotive Engineering 74
Replace Jaehyeon Kang with:
Jaehyeon Kang South Korea
Oliver Wulf Germany
Igor Bogoslavskyi Germany
Quang-Hieu Pham Singapore
Chongjian Yuan Hong Kong
Erke Shang China
Laksono Kurnianggoro South Korea
Zhixiong Ma China
Chiyu Dong United States
Chi Hay Tong Canada
Su Pang relative to Jaehyeon Kang South Korea Jaehyeon Kang's profile →
Citations per field
00.5×5.7×
Jaehyeon Kang · 1×
Citations per year

Countries citing papers authored by Su Pang

Since Specialization
Citations

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

Fields of papers citing papers by Su Pang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Su Pang, 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 Su Pang Line = papers co-authored together Su Pang links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1
CLOCs: Camera-LiDAR Object Candidates Fusion for 3D Object Detection
Hit paper breakdown →
2020323
2 202270
3 201329
4 201827
5 202314
6 202112
7 20219
8 20174
9 20183
10 20242
11
Advances in research on chemical constituents of Broussonetia plants and their pharmacological activities
20062
12 20241
13 20251
14 20191
15 20190

About Su Pang

Su Pang is a scholar working on Aerospace Engineering, Computer Vision and Pattern Recognition, Environmental Engineering, Electrical and Electronic Engineering and Ocean Engineering, having authored 15 papers that have together received 498 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (6 papers), Video Surveillance and Tracking Methods (3 papers), Geophysical Methods and Applications (3 papers), Advanced Neural Network Applications (3 papers), Vehicular Ad Hoc Networks (VANETs) (2 papers), Electromagnetic Simulation and Numerical Methods (2 papers), Remote Sensing and LiDAR Applications (2 papers) and Target Tracking and Data Fusion in Sensor Networks (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (364 citations), Instrumentation (46 citations), Aerospace Engineering (246 citations), Geology (53 citations) and Automotive Engineering (74 citations). Su Pang has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Hayder Radha, Daniel Morris, Xi Cai, Zhaoyang Bian, Gangling Tang, Xue Yang, Zheng Han, Yongsheng Ou, Xuben Wang and Xiangpeng Wang. Their work appears in journals such as Remote Sensing, Journal of Field Robotics, Scientific Reports, Journal of Chromatographic Science and SAE technical papers on CD-ROM/SAE technical paper series.

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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