What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Algorithm
- Statistics
Gabor T. Herman mainly focuses on Iterative reconstruction, Algorithm, Artificial intelligence, Computer vision and Tomography.
His studies deal with areas such as Image processing, Iterative method and Finite set as well as Iterative reconstruction.
His Algorithm research includes themes of Set, Algebraic number, Series expansion, Convolution and Projection.
The various areas that Gabor T. Herman examines in his Artificial intelligence study include Maximum a posteriori estimation and Pattern recognition.
His Tomography research is multidisciplinary, incorporating elements of Beam, Medical physics and Adjacency list.
Many of his research projects under Algebraic Reconstruction Technique are closely connected to Photography with Photography, tying the diverse disciplines of science together.
His most cited work include:
- Algebraic Reconstruction Techniques (ART) for three-dimensional electron microscopy and X-ray photography (2004 citations)
- Image reconstruction from projections : the fundamentals of computerized tomography (1716 citations)
- Image reconstruction from projections (944 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Algorithm, Artificial intelligence, Iterative reconstruction, Computer vision and Tomography.
His Algorithm research is multidisciplinary, incorporating perspectives in Image processing, Algebraic number, Projection, Mathematical optimization and Algebraic Reconstruction Technique.
The Artificial intelligence study which covers Pattern recognition that intersects with Prior probability.
In his research, Function is intimately related to Iterative method, which falls under the overarching field of Iterative reconstruction.
His Computer vision study combines topics from a wide range of disciplines, such as Surface, Computer graphics, Boundary and Interpolation.
His Tomographic reconstruction and Discrete tomography investigations are all subjects of Tomography research.
He most often published in these fields:
- Algorithm (33.57%)
- Artificial intelligence (32.63%)
- Iterative reconstruction (26.57%)
What were the highlights of his more recent work (between 2007-2020)?
- Algorithm (33.57%)
- Iterative reconstruction (26.57%)
- Artificial intelligence (32.63%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Algorithm, Iterative reconstruction, Artificial intelligence, Computer vision and Mathematical optimization.
His Algorithm study integrates concerns from other disciplines, such as Function, Point, Projection and Convex optimization.
His Iterative reconstruction research includes elements of Statistical hypothesis testing, Monotone polygon, Finite set, Conjugate gradient method and Proximal Gradient Methods.
His biological study spans a wide range of topics, including Tomography and Pattern recognition.
His research on Computer vision often connects related topics like Small number.
Gabor T. Herman works mostly in the field of Mathematical optimization, limiting it down to topics relating to Regular polygon and, in certain cases, Linear inequality and Limit of a sequence.
Between 2007 and 2020, his most popular works were:
- Fundamentals of Computerized Tomography: Image Reconstruction from Projections (454 citations)
- Fundamentals of Computerized Tomography (432 citations)
- Image reconstruction from a small number of projections (159 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Algorithm
- Statistics
His primary areas of study are Iterative reconstruction, Algorithm, Tomography, Artificial intelligence and Mathematical optimization.
His studies deal with areas such as Statistical hypothesis testing, Regular polygon, Proximal Gradient Methods, Computation and Compressed sensing as well as Iterative reconstruction.
His Algorithm study focuses on Iterative method in particular.
The various areas that he examines in his Tomography study include Constrained optimization, Soft x ray, Lens, Data acquisition and Medical physics.
His research integrates issues of Partition, Inverse problem, Computer vision and Pattern recognition in his study of Artificial intelligence.
His Mathematical optimization research incorporates elements of Sparse matrix, Process, Projection and Linear inequality.
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