What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
Du-Ming Tsai mostly deals with Artificial intelligence, Computer vision, Pattern recognition, Iterative reconstruction and Thresholding.
Artificial intelligence is frequently linked to Smoothing in his study.
His work in Computer vision is not limited to one particular discipline; it also encompasses Independent component analysis.
His Pattern recognition research is multidisciplinary, incorporating perspectives in Fuzzy number, Defuzzification, Object detection and Fuzzy classification.
His Iterative reconstruction research is multidisciplinary, incorporating elements of Basis and Texture.
His Thresholding research focuses on Balanced histogram thresholding and how it connects with Multi-swarm optimization, Gaussian blur and Image histogram.
His most cited work include:
- Independent Component Analysis-Based Background Subtraction for Indoor Surveillance (241 citations)
- Fast normalized cross correlation for defect detection (209 citations)
- Automated surface inspection for directional textures (165 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Artificial intelligence, Computer vision, Machine vision, Image processing and Pattern recognition.
His Artificial intelligence study deals with Liquid-crystal display intersecting with Image resolution.
Du-Ming Tsai works mostly in the field of Computer vision, limiting it down to topics relating to Basis and, in certain cases, Feature vector and Linear combination.
His work is dedicated to discovering how Machine vision, Visual inspection are connected with Line segment and other disciplines.
The various areas that Du-Ming Tsai examines in his Image processing study include Surface finish, Visual control, Artificial neural network, Object detection and Algorithm.
His work deals with themes such as Cross-correlation, Cluster analysis and Pattern matching, which intersect with Pattern recognition.
He most often published in these fields:
- Artificial intelligence (66.96%)
- Computer vision (53.57%)
- Machine vision (25.89%)
What were the highlights of his more recent work (between 2013-2021)?
- Artificial intelligence (66.96%)
- Computer vision (53.57%)
- Machine vision (25.89%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Artificial intelligence, Computer vision, Machine vision, Pixel and Image processing.
He frequently studies issues relating to Pattern recognition and Artificial intelligence.
The study incorporates disciplines such as Point and Edge in addition to Computer vision.
His research in Machine vision intersects with topics in Robot, Line, Real-time computing and Feature.
His Pixel study combines topics from a wide range of disciplines, such as Video tracking and Noise.
His Image processing research includes elements of Solar cell, Engineering drawing and Process engineering.
Between 2013 and 2021, his most popular works were:
- Optical flow-motion history image (OF-MHI) for action recognition (32 citations)
- A motion and image analysis method for automatic detection of estrus and mating behavior in cattle (29 citations)
- Machine Vision-Based Positioning and Inspection Using Expectation–Maximization Technique (22 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Geometry
Du-Ming Tsai mainly focuses on Artificial intelligence, Computer vision, Pixel, Feature vector and Segmentation.
Du-Ming Tsai interconnects Electronic engineering and Pattern recognition in the investigation of issues within Artificial intelligence.
His Computer vision research integrates issues from Invariant and Integrated circuit.
His biological study spans a wide range of topics, including Basis, Template matching, Surface reconstruction, Standard test image and Fourier transform.
His Segmentation research incorporates themes from Video tracking, Still camera, Background subtraction and Noise.
His studies in Machine vision integrate themes in fields like Image processing, Motion analysis and Region of interest.
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.
