World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
7747
World Ranking
12422
National Ranking
375

Overview

Hong Ren Wu is a researcher affiliated with RMIT University in Australia. Their academic work primarily spans the fields of Computer Science and Engineering, with a notable focus on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Mechanics of Materials, and Information Systems.

Their research covers a range of topics including Advanced Vision and Imaging, Image and Video Quality Assessment, Advanced Optical Imaging Technologies, Metal and Thin Film Mechanics, Blind Source Separation Techniques, Domain Adaptation and Few-Shot Learning, and Multimodal Machine Learning Applications.

Their recent publications include the following papers:

  • Progressive learning: A deep learning framework for continual learning (2020), Neural Networks
  • Quantization Parameter Cascading for Surveillance Video Coding Considering All Inter Reference Frames (2021), IEEE Transactions on Image Processing
  • Recognizing Induced Emotions With Only One Feature: A Novel Color Histogram-Based System (2020), IEEE Access
  • Depth Perception Assessment of 3D Videos Based on Stereoscopic and Spatial Orientation Structural Features (2022), IEEE Transactions on Circuits and Systems for Video Technology
  • An attempt to simulate structure and realistic images of scratches on rough polymeric surfaces (2020), Journal of Polymer Science

Hong Ren Wu's collaborative work involves frequent co-authors including Haytham M. Fayek, Jinjian Wu, Guangming Shi, Weimin Gao, and Lijing Wang. These partnerships have contributed to multiple projects and publications.

Their studies have been disseminated through various publication venues, with multiple entries in arXiv (Cornell University), Neural Networks, University Chemistry, IEEE Transactions on Image Processing, and IEEE Transactions on Circuits and Systems for Video Technology.

Best Publications

  • A robust MIMO terminal sliding mode control scheme for rigid robotic manipulators

    Man Zhihong;A.P. Paplinski;H.R. Wu

  • Adaptive impulse detection using center-weighted median filters

    T. Chen;Hong Ren Wu

  • Space variant median filters for the restoration of impulse noise corrupted images

    Tao Chen;Hong Ren Wu

  • A generalized block-edge impairment metric for video coding

    H.R. Wu;M. Yuen

  • Digital Video Image Quality and Perceptual Coding

    H.R. Wu;K.R. Rao

  • A survey of hybrid MC/DPCM/DCT video coding distortions

    Michael Yuen;H. R. Wu

  • Adaptive postfiltering of transform coefficients for the reduction of blocking artifacts

    T. Chen;H.R. Wu;B. Qiu

  • An adaptive tracking controller using neural networks for a class of nonlinear systems

    M. Zhihong;H.R. Wu;M. Palaniswami

  • Vision-model-based impairment metric to evaluate blocking artifacts in digital video

    Zhenghua Yu;Hong Ren Wu;S. Winkler;Tao Chen

  • Perceptual Color Image Coding With JPEG2000

    D.M. Tan;C.S. Tan;H.R. Wu

  • Efficient deinterlacing algorithm using edge-based line average interpolation

    Tao Chen;Hong Ren Wu;Zheng Hua Yu

  • A New Adaptive Backpropagation Algorithm Based on Lyapunov Stability Theory for Neural Networks

    Zhihong Man;Hong Ren Wu;Sophie Liu;Xinghuo Yu

  • No-Reference Quality Assessment for Networked Video via Primary Analysis of Bit Stream

    Fuzheng Yang;Shuai Wan;Qingpeng Xie;Hong Ren Wu

  • Reduced complexity PTS and new phase sequences for SLM to reduce PAP of an OFDM signal

    A.D.S. Jayalath;C. Tellambura;H. Wu

  • Facial Expression Recognition in Perceptual Color Space

    S. M. Lajevardi;Hong Ren Wu

  • A novel objective no-reference metric for digital video quality assessment

    Fuzheng Yang;Shuai Wan;Yilin Chang;Hong Ren Wu

  • Application of partition-based median type filters for suppressing noise in images

    Tao Chen;Hong Ren Wu

  • Perceptual Visual Signal Compression and Transmission

    Hong Ren Wu;A. R. Reibman;Weisi Lin;F. Pereira

  • A two-dimensional fast cosine transform algorithm based on Hou's approach

    H.R. Wu;F.J. Paoloni

  • Variable step-size LMS algorithm with a quotient form

    Shengkui Zhao;Zhihong Man;Suiyang Khoo;Hong Ren Wu

Frequent Co-Authors

Zhihong Man
Zhihong Man Swinburne University of Technology
Xinghuo Yu
Xinghuo Yu RMIT University
Weisi Lin
Weisi Lin Nanyang Technological University
Jiankun Hu
Jiankun Hu University of New South Wales
Chintha Tellambura
Chintha Tellambura University of Alberta
Dagan Feng
Dagan Feng University of Sydney
Amy R. Reibman
Amy R. Reibman Purdue University West Lafayette
Marimuthu Palaniswami
Marimuthu Palaniswami University of Melbourne
K. R. Rao
K. R. Rao The University of Texas at Arlington
Chun Tung Chou
Chun Tung Chou University of New South Wales

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