His primary scientific interests are in Artificial intelligence, Machine learning, Biometrics, Support vector machine and Pattern recognition. His study in Machine learning is interdisciplinary in nature, drawing from both Facial recognition system and Cognitive neuroscience of visual object recognition. His Facial recognition system study incorporates themes from Generalization and 3D single-object recognition.
His Biometrics study combines topics from a wide range of disciplines, such as Transformation, Computer network, Identity and Cryptography. He has researched Support vector machine in several fields, including Visualization, Training set, Psychophysics and Computer vision. Walter J. Scheirer combines subjects such as Normalization, Image retrieval, Fingerprint recognition and Image fusion with his study of Pattern recognition.
His scientific interests lie mostly in Artificial intelligence, Machine learning, Facial recognition system, Pattern recognition and Computer vision. All of his Artificial intelligence and Deep learning, Face, Convolutional neural network, Biometrics and Artificial neural network investigations are sub-components of the entire Artificial intelligence study. His Biometrics research is multidisciplinary, incorporating perspectives in Mobile device and Cryptography.
Walter J. Scheirer interconnects Bayesian probability, Cognitive neuroscience of visual object recognition, Visual Psychophysics and Random search in the investigation of issues within Machine learning. His work carried out in the field of Facial recognition system brings together such families of science as Image processing, Image retrieval and Set. His Pattern recognition research incorporates elements of Normalization and Face hallucination.
Walter J. Scheirer mainly investigates Artificial intelligence, Machine learning, Pattern recognition, Deep learning and Convolutional neural network. His work on Computer vision expands to the thematically related Artificial intelligence. In his research on the topic of Machine learning, Mixture model, Multivariate statistics, Inference and Covariate is strongly related with Bayesian probability.
His research on Pattern recognition also deals with topics like
Walter J. Scheirer mostly deals with Artificial intelligence, Machine learning, Convolutional neural network, Facial recognition system and Deep learning. His Artificial intelligence study integrates concerns from other disciplines, such as Psychophysics and Set. The various areas that Walter J. Scheirer examines in his Machine learning study include Stimulus, Visual Psychophysics, Random search and Machine translation.
His Facial recognition system research includes elements of Personally identifiable information and Biometrics. His research in Deep learning intersects with topics in Exploit, Backdoor and Robotics. His work deals with themes such as Machine vision and Human brain, which intersect with Cognitive neuroscience of visual object recognition.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Toward Open Set Recognition
W. J. Scheirer;A. de Rezende Rocha;A. Sapkota;T. E. Boult.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2013)
Cracking Fuzzy Vaults and Biometric Encryption
W.J. Scheirer;T.E. Boult.
The Bulletin of the Center for Children's Books (2007)
Probability Models for Open Set Recognition
Walter J. Scheirer;Lalit P. Jain;Terrance E. Boult.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2014)
Vision of the unseen: Current trends and challenges in digital image and video forensics
Anderson Rocha;Walter Scheirer;Terrance Boult;Siome Goldenstein.
ACM Computing Surveys (2011)
The limits and potentials of deep learning for robotics
Niko Sünderhauf;Oliver Brock;Walter J. Scheirer;Raia Hadsell.
The International Journal of Robotics Research (2018)
Revocable fingerprint biotokens: accuracy and security analysis
T. E. Boult;W. J. Scheirer;R. Woodworth.
computer vision and pattern recognition (2007)
Multi-attribute spaces: Calibration for attribute fusion and similarity search
Walter J. Scheirer;Neeraj Kumar;Peter N. Belhumeur;Terrance E. Boult.
computer vision and pattern recognition (2012)
Multi-class Open Set Recognition Using Probability of Inclusion
Lalit P. Jain;Walter J. Scheirer;Terrance E. Boult.
european conference on computer vision (2014)
Meta-Recognition: The Theory and Practice of Recognition Score Analysis
W J Scheirer;A Rocha;R J Micheals;T E Boult.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2011)
Authorship Attribution for Social Media Forensics
Anderson Rocha;Walter J. Scheirer;Christopher W. Forstall;Thiago Cavalcante.
IEEE Transactions on Information Forensics and Security (2017)
Profile was last updated on December 6th, 2021.
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