What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Cognition
His primary areas of study are Cognitive psychology, Perception, Cognition, Artificial intelligence and Facial expression.
His Cognitive psychology research includes elements of Social psychology, Face, Developmental psychology, Observer and Disgust.
The Perception study combines topics in areas such as Sensory system, Unobservable, Facial recognition system and Categorization.
His Cognition research incorporates themes from Stimulus and Occipitotemporal cortex.
He combines subjects such as Pattern recognition, Random field theory and Natural language processing with his study of Artificial intelligence.
His Facial expression research includes themes of Feature, Fixation and Mechanism.
His most cited work include:
- A mechanism for impaired fear recognition after amygdala damage (1032 citations)
- Controlling low-level image properties: the SHINE toolbox. (564 citations)
- Bubbles: a technique to reveal the use of information in recognition tasks (549 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Artificial intelligence, Cognitive psychology, Pattern recognition, Communication and Perception.
Frédéric Gosselin has researched Artificial intelligence in several fields, including Spatial frequency and Computer vision.
His Cognitive psychology research integrates issues from Social psychology, Electroencephalography, Cognition, Facial recognition system and Face.
The concepts of his Communication study are interwoven with issues in Visual perception and Reading.
His research investigates the connection with Perception and areas like Stimulus which intersect with concerns in Information processing.
In Facial expression, Frédéric Gosselin works on issues like Speech recognition, which are connected to Word recognition.
He most often published in these fields:
- Artificial intelligence (28.13%)
- Cognitive psychology (27.23%)
- Pattern recognition (16.07%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (28.13%)
- Cognitive psychology (27.23%)
- Pattern recognition (16.07%)
In recent papers he was focusing on the following fields of study:
Frédéric Gosselin mainly investigates Artificial intelligence, Cognitive psychology, Pattern recognition, Cognitive neuroscience of visual object recognition and Facial recognition system.
His studies deal with areas such as Multivariate statistics, Spatial frequency and Computer vision as well as Artificial intelligence.
His primary area of study in Cognitive psychology is in the field of Sensory system.
His Pattern recognition study integrates concerns from other disciplines, such as Identification, Visual recognition, Face, Sampling and Facial expression.
The study incorporates disciplines such as Emotion recognition, Eye tracking and Affect in addition to Facial expression.
He usually deals with Facial recognition system and limits it to topics linked to Communication and Utilization, Fixation and Form perception.
Between 2015 and 2021, his most popular works were:
- Eye fixation patterns for categorizing static and dynamic facial expressions. (24 citations)
- Culture shapes spatial frequency tuning for face identification. (22 citations)
- Greater reliance on the eye region predicts better face recognition ability (21 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Cognition
Frédéric Gosselin spends much of his time researching Cognitive psychology, Artificial intelligence, Facial recognition system, Pattern recognition and Spatial frequency.
His work investigates the relationship between Cognitive psychology and topics such as Eye movement that intersect with problems in Emotion recognition and Eye tracking.
His work on Cognitive neuroscience of visual object recognition as part of general Artificial intelligence research is frequently linked to Time course, bridging the gap between disciplines.
His Pattern recognition study combines topics in areas such as Facial expression, Categorization, Face perception and Identification.
He interconnects Orientation, Face and Pattern recognition in the investigation of issues within Facial expression.
His research integrates issues of Observer, Computer vision, Hand position and Communication in his study of Spatial frequency.
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