What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Facial expression, Facial recognition system and Computer vision.
His Artificial intelligence research focuses on Facial Action Coding System, Support vector machine, AdaBoost and Classifier.
The Pattern recognition study combines topics in areas such as Pixel, Cognition and Communication.
His Facial expression study which covers Speech recognition that intersects with Two-alternative forced choice.
His Facial recognition system research integrates issues from Machine learning, Feature, Independent component analysis, Gesture recognition and Principal component analysis.
Marian Stewart Bartlett works mostly in the field of Computer vision, limiting it down to topics relating to Coding and, in certain cases, Face hallucination.
His most cited work include:
- Face recognition by independent component analysis (1750 citations)
- Classifying facial actions (908 citations)
- Recognizing facial expression: machine learning and application to spontaneous behavior (514 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Artificial intelligence, Facial expression, Pattern recognition, Computer vision and Facial recognition system.
His research is interdisciplinary, bridging the disciplines of Machine learning and Artificial intelligence.
Marian Stewart Bartlett has researched Facial expression in several fields, including Facial expression recognition, Cognitive psychology and Speech recognition.
His Pattern recognition research incorporates themes from Supervised learning and Feature.
His Computer vision study combines topics in areas such as Hebbian theory and Learning rule.
His study focuses on the intersection of Facial recognition system and fields such as Gesture recognition with connections in the field of Three-dimensional face recognition.
He most often published in these fields:
- Artificial intelligence (73.20%)
- Facial expression (57.73%)
- Pattern recognition (39.18%)
What were the highlights of his more recent work (between 2013-2018)?
- Facial expression (57.73%)
- Artificial intelligence (73.20%)
- Pattern recognition (39.18%)
In recent papers he was focusing on the following fields of study:
Marian Stewart Bartlett spends much of his time researching Facial expression, Artificial intelligence, Pattern recognition, Discriminative model and Support vector machine.
He mostly deals with Facial Action Coding System in his studies of Facial expression.
His studies in Artificial intelligence integrate themes in fields like Computer vision and Natural language processing.
Marian Stewart Bartlett interconnects Machine learning and Cluster analysis in the investigation of issues within Pattern recognition.
His Discriminative model research is multidisciplinary, relying on both Time point, Frame, Bag-of-words model, Boosting and Visualization.
His Support vector machine study also includes
- Supervised learning which is related to area like Facial recognition system,
- Hidden Markov model which is related to area like Probability distribution, Probabilistic logic, Kernel and Classifier.
Between 2013 and 2018, his most popular works were:
- Automatic Decoding of Facial Movements Reveals Deceptive Pain Expressions (136 citations)
- Automated Assessment of Children's Postoperative Pain Using Computer Vision. (67 citations)
- LOMo: Latent Ordinal Model for Facial Analysis in Videos (47 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
Marian Stewart Bartlett mainly investigates Facial expression, Artificial intelligence, Pattern recognition, Discriminative model and Social relation.
His biological study spans a wide range of topics, including Developmental psychology, Autism, Typically developing and Autism spectrum disorder.
His Artificial intelligence research includes themes of Time point, Neurotypical and Affect.
He combines subjects such as Supervised learning, Facial recognition system and Facial analysis with his study of Pattern recognition.
His work carried out in the field of Discriminative model brings together such families of science as Frame, Cluster analysis, Bag-of-words model, Boosting and Visualization.
His Social relation study combines topics from a wide range of disciplines, such as Motor system, Speech recognition, Facial Action Coding System and Pattern recognition.
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