2023 - Research.com Computer Science in United States Leader Award
2020 - Fellow, National Academy of Inventors
2020 - Jack S. Kilby Signal Processing Medal For contributions to image and video processing
2015 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to Markov random fields, 3D recovery from single and mutiple images and image/video-based recognition
2013 - ACM Fellow For contributions to image processing, computer vision, and pattern recognition.
2012 - IAPR King-Sun Fu Prize For pioneering contributions to statistical methods for image- and video-based object recognition.
2011 - Fellow of the American Association for the Advancement of Science (AAAS)
2009 - OSA Fellows For pioneering and sustained contributions to image and video-based pattern recognition and computer vision.
1996 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to theory and applications of Markov Random Fields and computer vision
His main research concerns Artificial intelligence, Pattern recognition, Computer vision, Facial recognition system and Feature extraction. His Artificial intelligence study frequently draws connections between adjacent fields such as Machine learning. His research on Pattern recognition frequently links to adjacent areas such as Feature.
The concepts of his Computer vision study are interwoven with issues in Algorithm and Activity recognition. As a part of the same scientific study, Rama Chellappa usually deals with the Facial recognition system, concentrating on Subspace topology and frequently concerns with Linear discriminant analysis. His work in Feature extraction addresses subjects such as Pattern recognition, which are connected to disciplines such as Biometrics.
His primary scientific interests are in Artificial intelligence, Computer vision, Pattern recognition, Facial recognition system and Face. Artificial intelligence is closely attributed to Machine learning in his work. His Computer vision study frequently involves adjacent topics like Algorithm.
Rama Chellappa has included themes like Artificial neural network and Contextual image classification in his Pattern recognition study. His study in Facial recognition system is interdisciplinary in nature, drawing from both Pattern recognition and Biometrics. Face is frequently linked to Image in his study.
Rama Chellappa spends much of his time researching Artificial intelligence, Pattern recognition, Face, Facial recognition system and Machine learning. His work on Computer vision expands to the thematically related Artificial intelligence. His work in the fields of Classifier overlaps with other areas such as Set.
His study focuses on the intersection of Face and fields such as Authentication with connections in the field of Mobile device. His Machine learning research is multidisciplinary, incorporating perspectives in Adversarial system, Training set, Inference and Key. His Face detection study incorporates themes from Pose and Detector.
Rama Chellappa mostly deals with Artificial intelligence, Pattern recognition, Face, Convolutional neural network and Facial recognition system. His work deals with themes such as Machine learning and Computer vision, which intersect with Artificial intelligence. His biological study spans a wide range of topics, including Visualization, Representation, Cluster analysis and Robustness.
His Face research incorporates elements of Image, Pyramid, Expression and Authentication. His Convolutional neural network research is multidisciplinary, relying on both Artificial neural network, Pose and Benchmark. As a member of one scientific family, Rama Chellappa mostly works in the field of Facial recognition system, focusing on Pattern recognition and, on occasion, Baseline.
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.
Face recognition: A literature survey
W. Zhao;R. Chellappa;P. J. Phillips;A. Rosenfeld.
ACM Computing Surveys (2003)
Human and machine recognition of faces: a survey
R. Chellappa;C.L. Wilson;S. Sirohey.
Proceedings of the IEEE (1995)
Machine Recognition of Human Activities: A Survey
P. Turaga;R. Chellappa;V.S. Subrahmanian;O. Udrea.
IEEE Transactions on Circuits and Systems for Video Technology (2008)
Face recognition: A Literature Survey
W. Zhao;R. Rosenfeld;R. Chellappa.
ACM Computing Survey (2008)
Discriminant analysis for recognition of human face images
Kamran Etemad;Rama Chellappa.
Journal of The Optical Society of America A-optics Image Science and Vision (1997)
Human Action Recognition by Representing 3D Skeletons as Points in a Lie Group
Raviteja Vemulapalli;Felipe Arrate;Rama Chellappa.
computer vision and pattern recognition (2014)
A method for enforcing integrability in shape from shading algorithms
R.T. Frankot;R. Chellappa.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1988)
Estimation of illuminant direction, albedo, and shape from shading
Q. Zheng;R. Chellappa.
computer vision and pattern recognition (1991)
Discriminant analysis of principal components for face recognition
Wenyi Zhao;A. Krishnaswamy;R. Chellappa;D. L. Swets.
NATO ASI series. Series F : computer and system sciences (1998)
Domain adaptation for object recognition: An unsupervised approach
Raghuraman Gopalan;Ruonan Li;Rama Chellappa.
international conference on computer vision (2011)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: