What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Operating system
His scientific interests lie mostly in Artificial intelligence, Computer vision, Facial recognition system, Biometrics and Pattern recognition.
His Artificial intelligence study frequently involves adjacent topics like Matching.
His research in Computer vision intersects with topics in Machine learning and Data set.
His Facial recognition system study which covers Principal component analysis that intersects with Modality and Robustness.
His research integrates issues of Software deployment, Hamming distance and Iris in his study of Biometrics.
The concepts of his Pattern recognition study are interwoven with issues in Algorithm and Facial expression.
His most cited work include:
- Data clustering: a review (11332 citations)
- Overview of the face recognition grand challenge (2084 citations)
- Handbook of Biometrics (1016 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Artificial intelligence, Computer vision, Biometrics, Pattern recognition and Facial recognition system.
His Artificial intelligence study frequently links to other fields, such as Matching.
His research ties Pattern recognition and Computer vision together.
His studies deal with areas such as Data set, Robustness, Hamming distance, Principal component analysis and Data science as well as Biometrics.
His Pattern recognition study combines topics in areas such as Feature and Identification.
His research in the fields of Three-dimensional face recognition, Face detection and Face Recognition Grand Challenge overlaps with other disciplines such as Expression.
He most often published in these fields:
- Artificial intelligence (70.96%)
- Computer vision (50.60%)
- Biometrics (32.04%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (70.96%)
- Computer vision (50.60%)
- Face (19.76%)
In recent papers he was focusing on the following fields of study:
Patrick J. Flynn mostly deals with Artificial intelligence, Computer vision, Face, Facial recognition system and Pattern recognition.
His Artificial intelligence research integrates issues from Matching and Process.
When carried out as part of a general Computer vision research project, his work on Video camera is frequently linked to work in Sports science, therefore connecting diverse disciplines of study.
His Face research is multidisciplinary, incorporating perspectives in Machine learning and Convolutional neural network.
His Facial recognition system research incorporates elements of False accept rate, Mobile device and Solid modeling.
His work investigates the relationship between Object detection and topics such as Matching that intersect with problems in Cluster analysis.
Between 2015 and 2021, his most popular works were:
- On Low-Resolution Face Recognition in the Wild: Comparisons and New Techniques (44 citations)
- The ND-IRIS-0405 Iris Image Dataset. (42 citations)
- Crowd Scene Understanding from Video: A Survey (38 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Operating system
His primary areas of investigation include Artificial intelligence, Computer vision, Facial recognition system, Biometrics and Pattern recognition.
His Artificial intelligence research integrates issues from Process and Upload.
His research in Computer vision intersects with topics in Training set, Snapshot and Resolution.
His study with Facial recognition system involves better knowledge in Face.
His Biometrics research is multidisciplinary, incorporating perspectives in Data mining and Iris.
His work in Pattern recognition covers topics such as Iris recognition which are related to areas like Pupillary response, Dilation and Image matching.
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