What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Machine learning
His primary areas of study are Artificial intelligence, Pattern recognition, Handwriting, Handwriting recognition and Computer vision.
His research integrates issues of Speech recognition and Natural language processing in his study of Artificial intelligence.
His studies deal with areas such as Word recognition, Reading and Word as well as Natural language processing.
His Pattern recognition research is multidisciplinary, relying on both Contextual image classification and Machine learning.
The study incorporates disciplines such as Character, Segmentation, Sample and Sample in addition to Handwriting.
His Handwriting recognition study deals with Intelligent character recognition intersecting with Numeral system and Authentication.
His most cited work include:
- Online and off-line handwriting recognition: a comprehensive survey (2155 citations)
- Decision combination in multiple classifier systems (1409 citations)
- Off-line cursive script word recognition (430 citations)
What are the main themes of his work throughout his whole career to date?
Sargur N. Srihari mainly focuses on Artificial intelligence, Pattern recognition, Natural language processing, Speech recognition and Handwriting.
His studies in Artificial intelligence integrate themes in fields like Machine learning, Word recognition and Computer vision.
The various areas that he examines in his Pattern recognition study include Artificial neural network and Optical character recognition.
His study in Natural language processing is interdisciplinary in nature, drawing from both Intelligent character recognition, Character, Text segmentation and Reading.
His Speech recognition study integrates concerns from other disciplines, such as Image segmentation, Intelligent word recognition and Lexicon.
His Handwriting research incorporates elements of Feature and Identification.
He most often published in these fields:
- Artificial intelligence (70.12%)
- Pattern recognition (33.25%)
- Natural language processing (22.65%)
What were the highlights of his more recent work (between 2009-2021)?
- Artificial intelligence (70.12%)
- Pattern recognition (33.25%)
- Handwriting (17.83%)
In recent papers he was focusing on the following fields of study:
Sargur N. Srihari mostly deals with Artificial intelligence, Pattern recognition, Handwriting, Machine learning and Natural language processing.
All of his Artificial intelligence and Deep learning, Feature extraction, Artificial neural network, Bayesian probability and Graphical model investigations are sub-components of the entire Artificial intelligence study.
His research integrates issues of Identification, Word, Noise, Probabilistic logic and Minutiae in his study of Pattern recognition.
He combines subjects such as Cursive, Speech recognition, Feature and Handwriting recognition with his study of Handwriting.
His work in the fields of Machine learning, such as Leverage, overlaps with other areas such as Sensitivity.
His biological study spans a wide range of topics, including Context and Expert system.
Between 2009 and 2021, his most popular works were:
- Latent Print Examination and Human Factors: Improving the Practice through a Systems Approach (36 citations)
- Probabilistic graphical models in modern social network analysis (24 citations)
- Role of automation in the examination of handwritten items (19 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Machine learning
Sargur N. Srihari spends much of his time researching Artificial intelligence, Pattern recognition, Natural language processing, Handwriting and Crime scene.
Artificial intelligence connects with themes related to Computer vision in his study.
As a part of the same scientific study, Sargur N. Srihari usually deals with the Pattern recognition, concentrating on Noise and frequently concerns with Image restoration, Backpropagation, Categorization and Visualization.
His studies deal with areas such as Multimedia, Expert system, Interpretation, Fingerprint and Arabic as well as Natural language processing.
Many of his studies involve connections with topics such as Abstraction and Handwriting.
His research in Crime scene intersects with topics in Computational forensics, Feature extraction, Hough transform and Computer security.
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