R. Manmatha spends much of his time researching Artificial intelligence, Pattern recognition, Image retrieval, Search engine indexing and Natural language processing. R. Manmatha focuses mostly in the field of Artificial intelligence, narrowing it down to matters related to Computer vision and, in some cases, Redundancy. His work on Image segmentation, Dynamic time warping and Image texture as part of his general Pattern recognition study is frequently connected to Simple, thereby bridging the divide between different branches of science.
His studies deal with areas such as Feature and Cluster analysis as well as Image retrieval. His biological study spans a wide range of topics, including Feature detection and Feature vector. His Visual Word research incorporates elements of Information retrieval, Statistical model and Test set.
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Information retrieval, Image retrieval and Natural language processing. He focuses mostly in the field of Artificial intelligence, narrowing it down to topics relating to Computer vision and, in certain cases, Redundancy. His work deals with themes such as Contextual image classification and Histogram, which intersect with Pattern recognition.
His study explores the link between Information retrieval and topics such as World Wide Web that cross with problems in Focus. His research in Image retrieval is mostly focused on Visual Word. The study incorporates disciplines such as Data mining, Feature, Annotation, Feature detection and Image texture in addition to Automatic image annotation.
R. Manmatha focuses on Artificial intelligence, Machine learning, Pattern recognition, Deep learning and Image retrieval. His Artificial intelligence research incorporates themes from Computer vision and Natural language processing. His Feature vector study, which is part of a larger body of work in Pattern recognition, is frequently linked to Simple, bridging the gap between disciplines.
His Image retrieval study incorporates themes from Ranking, Field, Ranking and World Wide Web. His work in Automatic image annotation addresses subjects such as Annotation, which are connected to disciplines such as Discriminative model, Support vector machine and Search engine indexing. His Word study integrates concerns from other disciplines, such as Calibration, Information retrieval, Spotting and Text recognition.
His primary scientific interests are in Artificial intelligence, Machine learning, Pattern recognition, Block and Contextual image classification. His study looks at the relationship between Artificial intelligence and fields such as Computer vision, as well as how they intersect with chemical problems. His Machine learning study combines topics in areas such as Facial recognition system and Image retrieval.
He interconnects Annotation and Curse of dimensionality in the investigation of issues within Pattern recognition. His research in Contextual image classification intersects with topics in Class, Data mining, Disjoint sets and Benchmark. His Automatic image annotation research integrates issues from Relevance, Discriminative model and Support vector machine.
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.
Automatic image annotation and retrieval using cross-media relevance models
J. Jeon;V. Lavrenko;R. Manmatha.
international acm sigir conference on research and development in information retrieval (2003)
Multiple Bernoulli relevance models for image and video annotation
S.L. Feng;R. Manmatha;V. Lavrenko.
computer vision and pattern recognition (2004)
A Model for Learning the Semantics of Pictures
Victor Lavrenko;R. Manmatha;Jiwoon Jeon.
neural information processing systems (2003)
Word image matching using dynamic time warping
T.M. Rath;R. Manmatha.
computer vision and pattern recognition (2003)
Textfinder: an automatic system to detect and recognize text in images
V. Wu;R. Manmatha;E.M. Riseman.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1999)
Word spotting for historical documents
Toni M. Rath;R. Manmatha.
International Journal on Document Analysis and Recognition (2007)
Sampling Matters in Deep Embedding Learning
R. Manmatha;Chao-Yuan Wu;Alexander J. Smola;Philipp Krahenbuhl.
international conference on computer vision (2017)
Finding text in images
Victor Wu;R. Manmatha;Edward M. Riseman.
acm international conference on digital libraries (1997)
Word spotting: a new approach to indexing handwriting
R. Manmatha;Chengfeng Han;E.M. Riseman.
computer vision and pattern recognition (1996)
Features for word spotting in historical manuscripts
T.M. Rath;R. Manmatha.
international conference on document analysis and recognition (2003)
Profile was last updated on December 6th, 2021.
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