He Kong

1.5k citations
79 papers · 972 · h-index 17

Impact in

Papers in

He Kong

69 papers receiving 939 citations

Peers

He Kong
Comparison fields: 5 of 90
  • Small Animals 150
  • Control and Systems Engineering 249
  • Animal Science and Zoology 108
  • Food Science 177
  • Computer Vision and Pattern Recognition 197
Replace Daobilige Su with:
Daobilige Su Australia
Christos Tachtatzis United Kingdom
Philip Valencia Australia
Daihee Park South Korea
Thi Thi Zin Japan
Daniel Riordan Ireland
Henrik Karstoft Denmark
Amin Nasiri Iran
Leifeng Guo China
He Kong relative to Daobilige Su Australia Daobilige Su's profile →
Citations per field
00.5×4.9×
Daobilige Su · 1×
Citations per year

Countries citing papers authored by He Kong

Since Specialization
Citations

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

Fields of papers citing papers by He Kong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside He Kong, 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 He Kong Line = papers co-authored together He Kong links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021122
2 2021100
3 201967
4 202146
5 202142
6 201439
7 201935
8 199834
9 199632
10 202129
11 202027
12 202124
13 202021
14 202119
15 201819
16 202117
17 202017
18 201815
19 202215
20 201214

About He Kong

He Kong is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing and Mechanical Engineering, having authored 79 papers that have together received 972 indexed citations. Recurring topics across this work include Control Systems and Identification (15 papers), Advanced Control Systems Optimization (14 papers), Fault Detection and Control Systems (14 papers), Target Tracking and Data Fusion in Sensor Networks (8 papers), Speech and Audio Processing (7 papers), Animal Behavior and Welfare Studies (7 papers), Indoor and Outdoor Localization Technologies (6 papers) and Video Surveillance and Tracking Methods (5 papers). The work is most often cited by research in Small Animals (150 citations), Control and Systems Engineering (249 citations), Animal Science and Zoology (108 citations), Food Science (177 citations) and Computer Vision and Pattern Recognition (197 citations). He Kong has collaborated with scholars based in China, Australia and Hong Kong. Frequent co-authors include Salah Sukkarieh, Daobilige Su, Yongliang Qiao, Cameron Clark, Sabrina Lomax, Ling Guan, María M. Serón, Graham C. Goodwin, Galina Mirzaeva and Tianshi Chen. Their work appears in journals such as Automatica, IEEE Transactions on Automatic Control, IEEE Transactions on Circuits and Systems I Regular Papers, Computers and Electronics in Agriculture and IEEE/ASME Transactions on Mechatronics.

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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