Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
A robust MIMO terminal sliding mode control scheme for rigid robotic manipulators
1994775 citationsZhihong Man, Hong Ren Wu et al.profile →
Adaptive impulse detection using center-weighted median filters
This map shows the geographic impact of Hong Ren Wu'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 Hong Ren Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hong Ren Wu more than expected).
This network shows the impact of papers produced by Hong Ren Wu. 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 Hong Ren Wu. The network helps show where Hong Ren Wu may publish in the future.
Co-authorship network of co-authors of Hong Ren Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Hong Ren Wu.
A scholar is included among the top collaborators of Hong Ren Wu 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 Hong Ren Wu. Hong Ren Wu is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Qiu, Bin, et al.. (2003). An Adaptive Filter for Image Denoising using Fuzzy Inference.. 479–484.2 indexed citations
8.
Wu, Hong Ren, et al.. (2003). Perceptual lossless coding of digital monochrome images. 393–398.1 indexed citations
9.
Toncich, Dario, et al.. (2001). Vision based high accuracy work-piece inspection from profiles. Swinburne Research Bank (Swinburne University of Technology). 10(2). 155–174.1 indexed citations
10.
Wu, Hong Ren, et al.. (2001). Perceptual coding of digital colour images. 392–397.2 indexed citations
11.
Wu, Hong Ren, et al.. (2001). Impairment metrics for MC/DPCM/DCT encoded digital video. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 29–32.2 indexed citations
12.
Zhang, Man, et al.. (1999). A nonlinear Lyapunov RBF neural equalizer with its application to digital communication channel equalization. eCite Digital Repository (University of Tasmania).1 indexed citations
13.
Suthaharan, Shan & Hong Ren Wu. (1998). A New Linear Post-Filtering Technique to Reduce Transform Coding Block-Edge Artifact at Low Bit Rates. 120–128.
14.
Wu, Hong Ren, et al.. (1998). Multi-Dimensional Discrete Cosine Transform for Video Coding. 685–690.1 indexed citations
15.
Man, Zhihong, et al.. (1998). Design of Adaptive Filters Using Lyapunov Stability Theory. 304–308.13 indexed citations
16.
Suthaharan, Shan, Hong Ren Wu, & K.R. Rao. (1998). A New Edge Enhancement Technique for Image/ Video Segmentation and Compression. 748–751.1 indexed citations
17.
Wu, Hong Ren, et al.. (1997). Rate versus distortion comparison of fractal video techniques. 457–462.3 indexed citations
18.
Wu, Hong Ren, et al.. (1997). Implementation of Cho and Lee's 2D DCT algorithm using LLM 1D DCT algorithm. International Conference on Communications.2 indexed citations
19.
Wu, Hong Ren, et al.. (1997). Adaptive partitioning of three-dimensional fractal video. 381–385.
20.
Suthaharan, Shan & Hong Ren Wu. (1996). Adaptive. Neighbourhood Image Filtering for Mpeg-1 Coded Images. 1. 166–167.
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.