What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
His primary areas of investigation include Facial recognition system, Artificial intelligence, Biometrics, Spoofing attack and Computer security.
His Facial recognition system study deals with the bigger picture of Face.
His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning, Computer vision and Pattern recognition.
The Biometrics study which covers Fingerprint that intersects with Iris recognition.
His work in Spoofing attack tackles topics such as Image texture which are related to areas like Object detection and Attack model.
His Computer security study incorporates themes from Modality, Anti spoofing and Software deployment.
His most cited work include:
- On the effectiveness of local binary patterns in face anti-spoofing (398 citations)
- Person Authentication Using Brainwaves (EEG) and Maximum A Posteriori Model Adaptation (392 citations)
- Image Quality Assessment for Fake Biometric Detection: Application to Iris, Fingerprint, and Face Recognition (349 citations)
What are the main themes of his work throughout his whole career to date?
Sébastien Marcel mostly deals with Artificial intelligence, Facial recognition system, Biometrics, Face and Pattern recognition.
His Artificial intelligence study combines topics in areas such as Machine learning, Speech recognition and Computer vision.
Sébastien Marcel interconnects Convolutional neural network, Spoofing attack and Vulnerability in the investigation of issues within Facial recognition system.
His Biometrics research incorporates themes from Speaker recognition and Pattern recognition.
His study focuses on the intersection of Face and fields such as Authentication with connections in the field of The Internet.
The study incorporates disciplines such as Boosting, Local binary patterns and Perceptron in addition to Pattern recognition.
He most often published in these fields:
- Artificial intelligence (58.00%)
- Facial recognition system (40.00%)
- Biometrics (33.20%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (58.00%)
- Biometrics (33.20%)
- Facial recognition system (40.00%)
In recent papers he was focusing on the following fields of study:
Sébastien Marcel mainly investigates Artificial intelligence, Biometrics, Facial recognition system, Machine learning and Face.
His studies deal with areas such as Vulnerability, Computer vision and Pattern recognition as well as Artificial intelligence.
Biometrics is the subject of his research, which falls under Computer security.
The concepts of his Facial recognition system study are interwoven with issues in Spoofing attack, Word error rate, Morphing, RGB color model and Robustness.
His Machine learning research incorporates elements of Mixture model and Training set.
His study connects Authentication and Face.
Between 2018 and 2021, his most popular works were:
- Deep Pixel-wise Binary Supervision for Face Presentation Attack Detection (45 citations)
- Biometric Face Presentation Attack Detection With Multi-Channel Convolutional Neural Network (38 citations)
- Handbook of Biometric Anti-Spoofing: Presentation Attack Detection (31 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Computer vision
Sébastien Marcel focuses on Artificial intelligence, Facial recognition system, Convolutional neural network, Biometrics and Pattern recognition.
His research investigates the link between Artificial intelligence and topics such as Presentation that cross with problems in Computer vision, Pixel, Liveness and Statistical classification.
His Facial recognition system study combines topics from a wide range of disciplines, such as Machine learning and Vulnerability.
His Convolutional neural network research includes elements of Classifier and Feature extraction.
His Biometrics study introduces a deeper knowledge of Computer security.
In the field of Pattern recognition, his study on Discriminative model overlaps with subjects such as Short wave infrared and Research community.
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