What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
The scientist’s investigation covers issues in Biometrics, Artificial intelligence, Pattern recognition, Computer vision and Fingerprint.
Arun Ross has included themes like Fingerprint, Facial recognition system and Authentication in his Biometrics study.
His Artificial intelligence study which covers Machine learning that intersects with Normalization and Outlier.
In his research on the topic of Pattern recognition, Fingerprint Verification Competition is strongly related with Feature.
As part of the same scientific family, he usually focuses on Computer vision, concentrating on Iris and intersecting with Multispectral image.
His Fingerprint research incorporates elements of Matching, Speaker recognition and Matching.
His most cited work include:
- An introduction to biometric recognition (3687 citations)
- Score normalization in multimodal biometric systems (1508 citations)
- Information fusion in biometrics (1381 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Artificial intelligence, Biometrics, Pattern recognition, Computer vision and Iris recognition.
His study looks at the relationship between Artificial intelligence and topics such as Machine learning, which overlap with Classifier.
His research investigates the connection with Biometrics and areas like Data mining which intersect with concerns in Cluster analysis.
The study incorporates disciplines such as Matching, Image and Feature in addition to Pattern recognition.
His Iris recognition research includes themes of IRIS, Iris and Pupillary response.
His research on Fingerprint concerns the broader Computer security.
He most often published in these fields:
- Artificial intelligence (73.62%)
- Biometrics (53.68%)
- Pattern recognition (37.42%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (73.62%)
- Biometrics (53.68%)
- Pattern recognition (37.42%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Artificial intelligence, Biometrics, Pattern recognition, Face and Iris recognition.
His Artificial intelligence research includes elements of Machine learning, Computer vision and Presentation.
The Biometrics study combines topics in areas such as Spoofing attack, Human–computer interaction, Fingerprint, Liveness and Authentication.
His Pattern recognition research integrates issues from Fingerprint recognition and Generative adversarial network.
His studies examine the connections between Face and genetics, as well as such issues in Identification, with regards to Joint.
His Iris recognition study incorporates themes from Feature extraction and Iris.
Between 2018 and 2021, his most popular works were:
- A comprehensive overview of biometric fusion (42 citations)
- Some Research Problems in Biometrics: The Future Beckons (22 citations)
- FlowSAN: Privacy-Enhancing Semi-Adversarial Networks to Confound Arbitrary Face-Based Gender Classifiers (22 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
Arun Ross mainly focuses on Artificial intelligence, Biometrics, Pattern recognition, Iris recognition and Machine learning.
In the field of Artificial intelligence, his study on Classifier, Facial recognition system and Face overlaps with subjects such as Generalization.
His research investigates the link between Facial recognition system and topics such as Parsing that cross with problems in Pixel.
Arun Ross has researched Biometrics in several fields, including Password, Human–computer interaction, Fingerprint, Liveness and Authentication.
His Iris recognition research includes themes of IRIS, Convolutional neural network, Iris and Presentation.
His work carried out in the field of Machine learning brings together such families of science as Adversarial system and Scalability.
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