What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
Jeffrey F. Cohn spends much of his time researching Facial expression, Artificial intelligence, Facial recognition system, Speech recognition and Face.
His work on Facial Action Coding System as part of general Facial expression research is often related to Expression, thus linking different fields of science.
His Artificial intelligence study incorporates themes from Natural language processing, Computer vision and Pattern recognition.
The study incorporates disciplines such as Group method of data handling, Feature extraction, Kappa and Receiver operating characteristic in addition to Facial recognition system.
Jeffrey F. Cohn has researched Speech recognition in several fields, including Facial expression recognition, Probabilistic logic, Discrete emotions and Decision function.
His Face research incorporates themes from Gradient descent and Local search.
His most cited work include:
- Comprehensive database for facial expression analysis (2171 citations)
- The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression (2042 citations)
- Recognizing action units for facial expression analysis (1339 citations)
What are the main themes of his work throughout his whole career to date?
Jeffrey F. Cohn mainly investigates Artificial intelligence, Facial expression, Computer vision, Pattern recognition and Facial recognition system.
Artificial intelligence is often connected to Machine learning in his work.
His Facial Action Coding System study, which is part of a larger body of work in Facial expression, is frequently linked to Expression, bridging the gap between disciplines.
Many of his studies involve connections with topics such as Face hallucination and Pattern recognition.
A large part of his Facial recognition system studies is devoted to Face detection.
His studies in Developmental psychology integrate themes in fields like Social relation, Affect and Depression.
He most often published in these fields:
- Artificial intelligence (50.71%)
- Facial expression (47.86%)
- Computer vision (25.64%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (50.71%)
- Facial expression (47.86%)
- Pattern recognition (22.79%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Facial expression, Pattern recognition, Computer vision and Face.
His Artificial intelligence course of study focuses on Machine learning and Classifier.
Jeffrey F. Cohn has included themes like Field, Speech recognition, Face detection and Gesture recognition in his Facial expression study.
His work investigates the relationship between Face detection and topics such as Human–computer interaction that intersect with problems in Facial recognition system.
His work in Computer vision addresses issues such as Head, which are connected to fields such as Social relation.
He combines subjects such as Consistency, Artificial neural network, Partition and Rotation with his study of Face.
Between 2015 and 2021, his most popular works were:
- Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications (260 citations)
- Self-Adaptive Matrix Completion for Heart Rate Estimation from Face Videos under Realistic Conditions (160 citations)
- Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis (145 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
Artificial intelligence, Facial expression, Pattern recognition, Speech recognition and Face are his primary areas of study.
His study brings together the fields of Computer vision and Artificial intelligence.
His Facial expression research is multidisciplinary, incorporating elements of Field and Gesture recognition.
The concepts of his Speech recognition study are interwoven with issues in Major depressive disorder, Modalities and Facial Action Coding System.
His Face research includes elements of Consistency and Rotation.
His work deals with themes such as Classifier, Machine learning and Training set, which intersect with Feature extraction.
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