What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Algorithm
- Statistics
Rangasami L. Kashyap mainly focuses on Artificial intelligence, Computer vision, Algorithm, Autoregressive model and Feature extraction.
His studies in Artificial intelligence integrate themes in fields like Random field and Pattern recognition.
His study in Pattern recognition is interdisciplinary in nature, drawing from both Probability density function and Digital image processing.
His Computer vision study combines topics from a wide range of disciplines, such as Robot, Industrial robot and Point.
Rangasami L. Kashyap combines subjects such as Convergence and Application software with his study of Algorithm.
His Autoregressive model research incorporates elements of Data compression, Image compression, Moving average and Decision rule.
His most cited work include:
- Building skeleton models via 3-D medial surface/axis thinning algorithms (854 citations)
- Estimation and choice of neighbors in spatial-interaction models of images (396 citations)
- A Model-Based Method for Rotation Invariant Texture Classification (319 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Theoretical computer science.
His study in Artificial intelligence concentrates on Data compression, Image compression, Segmentation, Image processing and Image segmentation.
His research investigates the connection with Segmentation and areas like Video tracking which intersect with concerns in Search engine indexing.
His Computer vision study combines topics in areas such as Estimation theory and Polygon.
His Pattern recognition research is multidisciplinary, incorporating elements of Stochastic process, Pixel and Invariant.
Rangasami L. Kashyap focuses mostly in the field of Algorithm, narrowing it down to topics relating to Autoregressive model and, in certain cases, Decision rule.
He most often published in these fields:
- Artificial intelligence (47.59%)
- Computer vision (21.38%)
- Pattern recognition (18.62%)
What were the highlights of his more recent work (between 1995-2013)?
- Artificial intelligence (47.59%)
- Computer vision (21.38%)
- Multimedia database (4.83%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Computer vision, Multimedia database, Algorithm and Data compression.
In Artificial intelligence, Rangasami L. Kashyap works on issues like Pattern recognition, which are connected to Robust regression.
His Multimedia database research is multidisciplinary, relying on both Intelligent database, Data mining, Semantic data model and Database theory.
His Algorithm study incorporates themes from Basis and Syntactic pattern recognition.
The study incorporates disciplines such as Image resolution, Network congestion and Image quality in addition to Data compression.
As a member of one scientific family, Rangasami L. Kashyap mostly works in the field of Image processing, focusing on Speech processing and, on occasion, Robustness.
Between 1995 and 2013, his most popular works were:
- Video scene change detection method using unsupervised segmentation and object tracking (56 citations)
- A spatio-temporal semantic model for multimedia database systems and multimedia information systems (43 citations)
- IDENTIFYING OVERLAPPED OBJECTS FOR VIDEO INDEXING AND MODELING IN MULTIMEDIA DATABASE SYSTEMS (41 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Algorithm
- Statistics
His main research concerns Multimedia database, Search engine indexing, Video tracking, Multimedia and Partition.
Rangasami L. Kashyap is exploring Video tracking as part of his Artificial intelligence and Computer vision and Video tracking studies.
In his work, he performs multidisciplinary research in Artificial intelligence and Digital library.
His Computer vision study integrates concerns from other disciplines, such as Robot and Pattern recognition.
His Multimedia research incorporates themes from Information retrieval, Semantic data model, Spatial relation and Intelligent database.
His work carried out in the field of Partition brings together such families of science as Spatial analysis, Image segmentation, Scale-space segmentation and Theoretical computer science.
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