What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Algorithm
David Taubman focuses on Data compression, Artificial intelligence, Computer vision, Image compression and Algorithm.
The Data compression study combines topics in areas such as Image resolution, Quantization, Image processing, Discrete wavelet transform and Transform coding.
His biological study spans a wide range of topics, including Filter bank and Computer graphics.
Particularly relevant to JPEG 2000 is his body of work in Image compression.
His work carried out in the field of JPEG 2000 brings together such families of science as JPIP, The Internet and Set partitioning in hierarchical trees.
David Taubman has researched Algorithm in several fields, including Theoretical computer science and Sub-band coding.
His most cited work include:
- JPEG2000 : image compression fundamentals, standards, and practice (2728 citations)
- High performance scalable image compression with EBCOT (1870 citations)
- Multirate 3-D subband coding of video (576 citations)
What are the main themes of his work throughout his whole career to date?
David Taubman mainly investigates Artificial intelligence, Computer vision, Data compression, JPEG 2000 and Algorithm.
His work in Artificial intelligence addresses issues such as Scalability, which are connected to fields such as Server and Computer network.
David Taubman combines subjects such as Image processing, Image compression, Discrete wavelet transform and Video compression picture types with his study of Data compression.
His research in Image compression focuses on subjects like Computer hardware, which are connected to Embedded system.
His JPEG 2000 study integrates concerns from other disciplines, such as Transform coding, JPEG, JPIP and Block code.
His Algorithm research includes elements of Theoretical computer science, Filter and Sub-band coding.
He most often published in these fields:
- Artificial intelligence (46.77%)
- Computer vision (41.83%)
- Data compression (30.42%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (46.77%)
- Computer vision (41.83%)
- JPEG 2000 (25.86%)
In recent papers he was focusing on the following fields of study:
David Taubman mainly focuses on Artificial intelligence, Computer vision, JPEG 2000, Algorithm and Transform coding.
The concepts of his Artificial intelligence study are interwoven with issues in Scalability and Pattern recognition.
The various areas that David Taubman examines in his Computer vision study include Affine transformation, Reference frame and Interpolation.
To a larger extent, David Taubman studies Image compression with the aim of understanding JPEG 2000.
In his study, Regular polygon is strongly linked to Distortion, which falls under the umbrella field of Algorithm.
His Transform coding research is multidisciplinary, relying on both Decoding methods and Lossless compression.
Between 2015 and 2021, his most popular works were:
- Responsive high throughput congestion control for interactive applications over SDN-enabled networks (15 citations)
- A Novel Motion Field Anchoring Paradigm for Highly Scalable Wavelet-Based Video Coding (11 citations)
- COGL: Coefficient Graph Laplacians for Optimized JPEG Image Decoding (9 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Algorithm
His primary areas of investigation include Artificial intelligence, Computer vision, Motion estimation, Motion field and Transform coding.
His research in Artificial intelligence intersects with topics in Surface reconstruction, Algorithm, Current and Pattern recognition.
David Taubman has included themes like Albedo and System of linear equations in his Algorithm study.
In his study, Motion interpolation, Block-matching algorithm, Motion compensation and Quarter-pixel motion is inextricably linked to Reference frame, which falls within the broad field of Computer vision.
His Transform coding research incorporates themes from JPEG, Image compression, JPEG 2000, Decoding methods and Wavelet.
His work deals with themes such as Lifting scheme, Wavelet packet decomposition, Lossy compression, Lossless compression and Set partitioning in hierarchical trees, which intersect with JPEG 2000.
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