What is he best known for?
The fields of study Guoyin Wang is best known for:
- Zernike polynomials
- Image moment
- Velocity Moments
His Artificial intelligence study frequently links to other fields, such as Classifier (UML).
Many of his studies on Pattern recognition (psychology) involve topics that are commonly interrelated, such as Artificial intelligence.
Guoyin Wang integrates many fields, such as Rough set and Data mining, in his works.
In his works, Guoyin Wang conducts interdisciplinary research on Data mining and Rough set.
As part of his studies on Programming language, Guoyin Wang often connects relevant areas like Set (abstract data type).
Guoyin Wang combines topics linked to Programming language with his work on Set (abstract data type).
His Labeled data study frequently links to other fields, such as Machine learning.
His study on Machine learning is mostly dedicated to connecting different topics, such as Labeled data.
In his works, he undertakes multidisciplinary study on Support vector machine and Artificial neural network.
His most cited work include:
- A Survey on Rough Set Theory and Applications (89 citations)
- Self-training semi-supervised classification based on density peaks of data (67 citations)
- Radial shifted Legendre moments for image analysis and invariant image recognition (48 citations)
What are the main themes of his work throughout his whole career to date
In his research, Guoyin Wang undertakes multidisciplinary study on Artificial intelligence and Algorithm.
Guoyin Wang undertakes interdisciplinary study in the fields of Algorithm and Artificial intelligence through his research.
He undertakes interdisciplinary study in the fields of Rough set and Data mining through his research.
Guoyin Wang performs multidisciplinary study in the fields of Data mining and Rough set via his papers.
His research combines Set (abstract data type) and Programming language.
Many of his studies on Set (abstract data type) involve topics that are commonly interrelated, such as Programming language.
Borrowing concepts from Cloud computing, he weaves in ideas under Operating system.
He carries out multidisciplinary research, doing studies in Cloud computing and Operating system.
He frequently studies issues relating to Computer vision and Image (mathematics).
Guoyin Wang most often published in these fields:
- Artificial intelligence (65.22%)
- Rough set (26.09%)
- Data mining (21.74%)
What were the highlights of his more recent work (between 2017-2022)?
- Artificial intelligence (100.00%)
- Training set (50.00%)
- Machine learning (50.00%)
In recent works Guoyin Wang was focusing on the following fields of study:
His Artificial intelligence study frequently intersects with other fields, such as Pattern recognition (psychology).
Pattern recognition (psychology) is closely attributed to Artificial intelligence in his study.
His Labeled data research extends to the thematically linked field of Machine learning.
Guoyin Wang combines topics linked to Machine learning with his work on Labeled data.
In his articles, he combines various disciplines, including Artificial neural network and Data mining.
While working in this field, he studies both Data mining and Artificial neural network.
In his research, he undertakes multidisciplinary study on Supervised learning and Support vector machine.
Guoyin Wang carries out multidisciplinary research, doing studies in Support vector machine and Supervised learning.
Guoyin Wang incorporates Mobile computing and Mobile edge computing in his research.
Between 2017 and 2022, his most popular works were:
- Self-training semi-supervised classification based on density peaks of data (67 citations)
- Mean-Field Learning for Edge Computing in Mobile Blockchain Networks (6 citations)
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