Chee-Way Chong

821 total citations
11 papers, 585 citations indexed

About

Chee-Way Chong is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology and Civil and Structural Engineering. According to data from OpenAlex, Chee-Way Chong has authored 11 papers receiving a total of 585 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 1 paper in Molecular Biology and 1 paper in Civil and Structural Engineering. Recurrent topics in Chee-Way Chong's work include Image Retrieval and Classification Techniques (9 papers), Advanced Image and Video Retrieval Techniques (9 papers) and Medical Image Segmentation Techniques (7 papers). Chee-Way Chong is often cited by papers focused on Image Retrieval and Classification Techniques (9 papers), Advanced Image and Video Retrieval Techniques (9 papers) and Medical Image Segmentation Techniques (7 papers). Chee-Way Chong collaborates with scholars based in Malaysia, New Zealand and China. Chee-Way Chong's co-authors include Ramakrishnan Mukundan, Raveendran Paramesran, Rosli Besar, Fazly Salleh Abas, Xingwei Zhao, Peng Fu and Hongtai Yang and has published in prestigious journals such as Pattern Recognition, Electronics and Pattern Analysis and Applications.

In The Last Decade

Chee-Way Chong

10 papers receiving 535 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Chee-Way Chong Malaysia	7	504	97	38	33	30	11	585
S.X. Liao Canada	9	612 1.2×	103 1.1×	73 1.9×	20 0.6×	29 1.0×	13	691
Ziliang Ping China	10	423 0.8×	125 1.3×	22 0.6×	11 0.3×	17 0.6×	27	458
Zhenqiu Shu China	14	408 0.8×	116 1.2×	138 3.6×	25 0.8×	26 0.9×	69	587
I.A. Esquef Brazil	4	298 0.6×	149 1.5×	76 2.0×	10 0.3×	8 0.3×	9	415
Abdullah Bal Türkiye	11	175 0.3×	173 1.8×	64 1.7×	11 0.3×	26 0.9×	49	385
Zhen Lou China	7	304 0.6×	80 0.8×	70 1.8×	24 0.7×	75 2.5×	21	408
Yongwei Li China	10	374 0.7×	164 1.7×	37 1.0×	13 0.4×	16 0.5×	22	428
Glen P. Abousleman United States	11	403 0.8×	116 1.2×	55 1.4×	12 0.4×	80 2.7×	62	497
W.C. Siu Hong Kong	12	338 0.7×	64 0.7×	62 1.6×	44 1.3×	87 2.9×	33	469
D. Guillamet Spain	9	175 0.3×	51 0.5×	72 1.9×	20 0.6×	104 3.5×	13	320

Countries citing papers authored by Chee-Way Chong

Since Specialization

Citations

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

Fields of papers citing papers by Chee-Way Chong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chee-Way Chong. 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-Way Chong. The network helps show where Chee-Way Chong may publish in the future.

Co-authorship network of co-authors of Chee-Way Chong

This figure shows the co-authorship network connecting the top 25 collaborators of Chee-Way Chong. A scholar is included among the top collaborators of Chee-Way Chong 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 Chee-Way Chong. Chee-Way Chong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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11 of 11 papers shown

1.

Fu, Peng, et al.. (2025). Multi-Feature Fusion YOLO Approach for Fault Detection and Location of Train Running Section. Electronics. 14(17). 3430–3430.

2.

Chong, Chee-Way, et al.. (2009). TRANSLATION AND SCALE INVARIANTS OF HAHN MOMENTS. International Journal of Image and Graphics. 9(2). 271–285. 13 indexed citations

3.

Chong, Chee-Way, et al.. (2007). An approach to 3-D object recognition using Legendre moment invariants. 671–674. 3 indexed citations

4.

Chong, Chee-Way, et al.. (2006). Scale Invariants of Three-Dimensional Legendre Moments. 3. 141–144. 4 indexed citations

5.

Chong, Chee-Way, et al.. (2006). Scale Invariants of Three-Dimensional Legendre Moments. 34. 1–4. 3 indexed citations

6.

Chong, Chee-Way, Raveendran Paramesran, & Ramakrishnan Mukundan. (2003). Translation and scale invariants of Legendre moments. Pattern Recognition. 37(1). 119–129. 134 indexed citations

7.

Chong, Chee-Way, Raveendran Paramesran, & Ramakrishnan Mukundan. (2003). The scale invariants of pseudo-Zernike moments. Pattern Analysis and Applications. 6(3). 176–184. 65 indexed citations

8.

Chong, Chee-Way, Raveendran Paramesran, & Ramakrishnan Mukundan. (2003). An Efficient Algorithm for Fast Computation of Pseudo-Zernike Moments. International Journal of Pattern Recognition and Artificial Intelligence. 17(6). 1011–1023. 61 indexed citations

9.

Chong, Chee-Way, Raveendran Paramesran, & Ramakrishnan Mukundan. (2003). Translation invariants of Zernike moments. Pattern Recognition. 36(8). 1765–1773. 108 indexed citations

10.

Chong, Chee-Way, Ramakrishnan Mukundan, & Raveendran Paramesran. (2002). An Efficient Algorithm for Fast Computation of Zernike Moments. 785–788. 9 indexed citations

11.

Chong, Chee-Way, Raveendran Paramesran, & Ramakrishnan Mukundan. (2002). A comparative analysis of algorithms for fast computation of Zernike moments. Pattern Recognition. 36(3). 731–742. 185 indexed citations

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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