What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Optics
- Computer vision
Michael A. Webster mostly deals with Optics, Adaptation, Perception, Color vision and Chromatic scale.
Within one scientific family, Michael A. Webster focuses on topics pertaining to Artificial intelligence under Optics, and may sometimes address concerns connected to Stimulus luminance.
In his research on the topic of Adaptation, Visual sensitivity is strongly related with Computer vision.
His Perception study combines topics from a wide range of disciplines, such as Cognitive psychology, Cognitive science and Communication.
Michael A. Webster has included themes like Chromaticity, Degree, Hue and Color space in his Color vision study.
His work deals with themes such as Perceptual Distortion, Form perception and Face, which intersect with Face perception.
His most cited work include:
- Adaptation to natural facial categories (526 citations)
- Figural aftereffects in the perception of faces (347 citations)
- Visual adaptation: neural, psychological and computational aspects. (263 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial intelligence, Optics, Computer vision, Color vision and Perception.
Michael A. Webster has researched Artificial intelligence in several fields, including Adaptation and Pattern recognition.
His work on Luminance, Spatial frequency and Spectral sensitivity is typically connected to Color difference as part of general Optics study, connecting several disciplines of science.
His Computer vision research integrates issues from Focus and Visual adaptation.
His study looks at the relationship between Color vision and topics such as Hue, which overlap with Scaling.
He combines subjects such as Stimulus, Cognitive psychology and Cognition with his study of Perception.
He most often published in these fields:
- Artificial intelligence (36.74%)
- Optics (27.27%)
- Computer vision (25.00%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (36.74%)
- Color vision (25.00%)
- Computer vision (25.00%)
In recent papers he was focusing on the following fields of study:
Michael A. Webster spends much of his time researching Artificial intelligence, Color vision, Computer vision, Adaptation and Perception.
His work focuses on many connections between Artificial intelligence and other disciplines, such as Pattern recognition, that overlap with his field of interest in Hue, Stimulus and Electroencephalography.
His Color vision study introduces a deeper knowledge of Optics.
His research integrates issues of Illusion and Shading in his study of Computer vision.
His studies deal with areas such as Peripheral vision and Eccentricity as well as Adaptation.
His research in Perception tackles topics such as Decoding methods which are related to areas like Magnetoencephalography and Speech recognition.
Between 2017 and 2021, his most popular works were:
- Individual differences and their implications for color perception. (11 citations)
- All-or-none face categorization in the human brain (8 citations)
- Dissociable effects of inter-stimulus interval and presentation duration on rapid face categorization. (8 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Optics
- Computer vision
Perception, Color vision, Hue, Pattern recognition and Artificial intelligence are his primary areas of study.
As a member of one scientific family, Michael A. Webster mostly works in the field of Perception, focusing on Cognitive psychology and, on occasion, Spectral sensitivity and Color-coding.
His Color vision research is classified as research in Optics.
His work carried out in the field of Hue brings together such families of science as Color space, Trichromacy, Salience, Chromatic scale and Scaling.
His Pattern recognition research includes themes of Electroencephalography, Stimulus, Contrast, Facial expression and Invariant.
His work on Facial recognition system, Color constancy and Pixel as part of general Artificial intelligence research is often related to Expression, thus linking different fields of science.
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.
