What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Algorithm
- Computer vision
Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Image processing are his primary areas of study.
Artificial intelligence is a component of his Motion compensation, Motion estimation, Pixel, Block-matching algorithm and Image studies.
Face, Feature extraction, Data compression, Image quality and Discrete cosine transform are among the areas of Computer vision where the researcher is concentrating his efforts.
The Pattern recognition study combines topics in areas such as Function, Image moment, Random forest and Character recognition.
Wan-Chi Siu has researched Algorithm in several fields, including Image resolution, Covariance, Edge detection and Additive model.
His Image processing study combines topics from a wide range of disciplines, such as Luminance, Image segmentation and Interpolation.
His most cited work include:
- Single image super-resolution using Gaussian process regression (203 citations)
- An efficient algorithm for human face detection and facial feature extraction under different conditions (134 citations)
- A technique for extracting physiological parameters and the required input function simultaneously from PET image measurements: theory and simulation study (129 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial intelligence, Computer vision, Algorithm, Pattern recognition and Motion estimation.
His study in Motion compensation, Data compression, Feature extraction, Pixel and Image processing is carried out as part of his studies in Artificial intelligence.
He combines subjects such as Coding tree unit and Transcoding with his study of Computer vision.
The various areas that Wan-Chi Siu examines in his Algorithm study include Coding, Mathematical optimization and Discrete cosine transform.
Particularly relevant to Image segmentation is his body of work in Pattern recognition.
His Motion estimation research is multidisciplinary, incorporating elements of Reference frame and Search algorithm.
He most often published in these fields:
- Artificial intelligence (58.43%)
- Computer vision (42.97%)
- Algorithm (39.96%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (58.43%)
- Computer vision (42.97%)
- Pattern recognition (20.28%)
In recent papers he was focusing on the following fields of study:
Wan-Chi Siu mainly investigates Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Coding.
His Artificial intelligence study focuses mostly on Feature extraction, Superresolution, Deep learning, Image and Motion estimation.
He works in the field of Computer vision, namely Block-matching algorithm.
His study in Pattern recognition is interdisciplinary in nature, drawing from both Decision tree, Random forest, Decoding methods and Feature.
When carried out as part of a general Algorithm research project, his work on Fast mode is frequently linked to work in Hash function, therefore connecting diverse disciplines of study.
His study on Coding tree unit, Coding gain and Intra mode is often connected to View synthesis and Merge as part of broader study in Coding.
Between 2015 and 2021, his most popular works were:
- Learning Hierarchical Decision Trees for Single-Image Super-Resolution (42 citations)
- NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results (33 citations)
- Probability-Based Depth Intra-Mode Skipping Strategy and Novel VSO Metric for DMM Decision in 3D-HEVC (22 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Algorithm
- Statistics
His main research concerns Artificial intelligence, Algorithm, Coding, Computer vision and Image resolution.
His research on Artificial intelligence often connects related topics like Pattern recognition.
His Algorithm research incorporates themes from Change detection, Encoder, Bayesian probability and Decision rule.
His research integrates issues of Pixel, Fast mode and Speech processing in his study of Coding.
His research in Computer vision focuses on subjects like Protocol, which are connected to Image restoration, Metric and Measure.
His studies in Depth map integrate themes in fields like Motion estimation, Multiview Video Coding, Coding tree unit and Algorithmic efficiency.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
