What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
Gregory J. Zelinsky focuses on Eye movement, Communication, Visual search, Perception and Artificial intelligence.
His Eye movement study combines topics from a wide range of disciplines, such as Cognitive psychology and Psychophysics.
As part of the same scientific family, Gregory J. Zelinsky usually focuses on Communication, concentrating on Working memory and intersecting with Salience and Cognitive science.
His work carried out in the field of Visual search brings together such families of science as Visual perception, Categorization and Gaze.
His studies examine the connections between Perception and genetics, as well as such issues in Cognition, with regards to Cued speech and Scene statistics.
His Artificial intelligence research incorporates elements of Computer vision and Pattern recognition.
His most cited work include:
- A theory of eye movements during target acquisition. (289 citations)
- Influence of attentional capture on oculomotor control (277 citations)
- Scene context guides eye movements during visual search. (239 citations)
What are the main themes of his work throughout his whole career to date?
Artificial intelligence, Visual search, Eye movement, Computer vision and Communication are his primary areas of study.
Gregory J. Zelinsky has researched Artificial intelligence in several fields, including Natural language processing, Categorical variable and Pattern recognition.
His Visual search research incorporates themes from Speech recognition, Gaze-contingency paradigm and Similarity.
His Eye movement study integrates concerns from other disciplines, such as Perception and Visual memory.
His work carried out in the field of Perception brings together such families of science as Segmentation and Cognition.
His studies deal with areas such as Cued speech, Working memory, Visual perception, Set and Psychophysics as well as Communication.
He most often published in these fields:
- Artificial intelligence (63.31%)
- Visual search (38.46%)
- Eye movement (32.54%)
What were the highlights of his more recent work (between 2016-2021)?
- Artificial intelligence (63.31%)
- Attentional control (5.92%)
- Machine learning (4.73%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Artificial intelligence, Attentional control, Machine learning, Visual search and Computer vision.
Artificial intelligence connects with themes related to Pattern recognition in his study.
His biological study spans a wide range of topics, including Saccade, Communication and Fixation.
The concepts of his Visual search study are interwoven with issues in Feature, Encoding, Hue, Visual Physiology and Categorical variable.
In his research, Cognitive psychology, Support vector machine and Classifier is intimately related to Eye movement, which falls under the overarching field of Categorical variable.
In the field of Computer vision, his study on Object control overlaps with subjects such as Gaussian.
Between 2016 and 2021, his most popular works were:
- A Model of the Superior Colliculus Predicts Fixation Locations during Scene Viewing and Visual Search. (28 citations)
- Adding details to the attentional template offsets search difficulty: Evidence from contralateral delay activity. (10 citations)
- Co-localization with Category-Consistent Features and Geodesic Distance Propagation (9 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Computer vision
His main research concerns Artificial intelligence, Eye movement, Visual search, Machine learning and Fixation.
Gregory J. Zelinsky interconnects Attentional control and Pattern recognition in the investigation of issues within Artificial intelligence.
His work in the fields of Feature extraction overlaps with other areas such as Co localization.
His Eye movement study combines topics from a wide range of disciplines, such as Speech recognition and Communication.
His Communication study frequently draws parallels with other fields, such as Computational model.
His Visual search research includes elements of Feature, Encoding, Gaze, Task analysis and Visualization.
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