What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Statistics
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 most cited work include:
- Face recognition: A literature survey (5777 citations)
- Human and machine recognition of faces: a survey (2358 citations)
- Machine Recognition of Human Activities: A Survey (1142 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, 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.
He most often published in these fields:
- Artificial intelligence (81.65%)
- Computer vision (47.05%)
- Pattern recognition (34.13%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (81.65%)
- Pattern recognition (34.13%)
- Face (14.54%)
In recent papers he was focusing on the following fields of 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.
Between 2015 and 2021, his most popular works were:
- HyperFace: A Deep Multi-Task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition (695 citations)
- Soft-NMS — Improving Object Detection with One Line of Code (416 citations)
- Generate to Adapt: Aligning Domains Using Generative Adversarial Networks (326 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Statistics
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.
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