Chee Kit Wong

445 citations
12 papers · 281 · h-index 6

Impact in

Papers in

Chee Kit Wong

12 papers receiving 262 citations

Peers

Chee Kit Wong
Comparison fields: 5 of 66
  • Computer Vision and Pattern Recognition 132
  • Media Technology 50
  • Mathematical Physics 50
  • Applied Mathematics 37
  • Modeling and Simulation 15
Replace Yuanyuan Huang with:
Yuanyuan Huang China
Hyenkyun Woo South Korea
Agnieszka Lisowska Poland
Marko Janev Serbia
L. K. Balyan India
François Malgouyres France
Chih-Fan Chen United States
Samuel Vaiter France
Zhenyu Zhao China
Paul Burchard United States
Chee Kit Wong relative to Yuanyuan Huang China Yuanyuan Huang's profile →
Citations per field
00.5×9.3×
Yuanyuan Huang · 1×
Citations per year

Countries citing papers authored by Chee Kit Wong

Since Specialization
Citations

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

Fields of papers citing papers by Chee Kit Wong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chee Kit Wong. 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 Chee Kit Wong. The network helps show where Chee Kit Wong may publish in the future.

Co-authors

The 14 scholars most cited alongside Chee Kit Wong, 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 Chee Kit Wong Line = papers co-authored together Chee Kit Wong links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2002142
2 200076
3 202030
4 20119
5
Using a mobile robot for cognitive mapping
20077
6 20066
7
A Mobile Robot that Maps Naively But Plans Intelligently
20053
8 20142
9
Vision system for the automation of ovine carcass processing
20142
10
Vision Strategies for Robotic Manipulation of Natural Objects
20092
11
Processing of point cloud data from ToF camera for the localisation of ground-based crop
20121
12 20061

About Chee Kit Wong

Chee Kit Wong is a scholar working on Aerospace Engineering, Computer Vision and Pattern Recognition, Automotive Engineering, Computational Mechanics and Artificial Intelligence, having authored 12 papers that have together received 281 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (5 papers), Spatial Cognition and Navigation (3 papers), 3D Surveying and Cultural Heritage (2 papers), Image and Signal Denoising Methods (2 papers), Sparse and Compressive Sensing Techniques (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Smart Agriculture and AI (2 papers) and Advanced Image Processing Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (132 citations), Media Technology (50 citations), Mathematical Physics (50 citations), Applied Mathematics (37 citations) and Modeling and Simulation (15 citations). Chee Kit Wong has collaborated with scholars based in New Zealand and United States. Frequent co-authors include Tony F. Chan, Pep Mulet, Peter Blomgren, Jochen Schmidt, Pey Lian Lim, Mustafa M. Farouk, Marlon M. Reis, Marcus King, Talia M. Hicks and Wai K. Yeap. Their work appears in journals such as Meat Science, Linear Algebra and its Applications, International Journal of Computer Applications in Technology, PubMed and Rare & Special e-Zone (The Hong Kong University of Science and Technology).

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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