What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Algorithm
- Programming language
His primary areas of investigation include Augmented reality, Artificial intelligence, Computer vision, Graphics and Computer graphics.
His work deals with themes such as Object and Video camera, which intersect with Augmented reality.
His study in the field of Level set, Morphing and Interpolation is also linked to topics like Data modeling.
His Computer vision research incorporates elements of Surface and Level set.
His Computer graphics study frequently draws parallels with other fields, such as Mechanical engineering.
His Geometry research is multidisciplinary, incorporating elements of Algorithm and Set.
His most cited work include:
- Predicting the drape of woven cloth using interacting particles (344 citations)
- Interactive Occlusion and Collision of Real and Virtual Objects in Augmented Reality (287 citations)
- Level set surface editing operators (239 citations)
What are the main themes of his work throughout his whole career to date?
David E. Breen focuses on Artificial intelligence, Computer graphics, Computer vision, Algorithm and Surface.
The various areas that David E. Breen examines in his Artificial intelligence study include Process and Pattern recognition.
In his study, User interface and Computational science is inextricably linked to Visualization, which falls within the broad field of Computer graphics.
The Computer vision study which covers Surface reconstruction that intersects with Wing.
His work focuses on many connections between Algorithm and other disciplines, such as Geometric modeling, that overlap with his field of interest in Polygon and Topology.
His Surface research also works with subjects such as
- Set which is related to area like Point, Level set, Level set, Level set method and Data set,
- Interpolation which connect with Similarity.
He most often published in these fields:
- Artificial intelligence (27.20%)
- Computer graphics (20.00%)
- Computer vision (20.00%)
What were the highlights of his more recent work (between 2016-2021)?
- Artificial intelligence (27.20%)
- Yarn (4.00%)
- Finite element method (4.80%)
In recent papers he was focusing on the following fields of study:
David E. Breen mostly deals with Artificial intelligence, Yarn, Finite element method, Materials science and Biological system.
The study of Artificial intelligence is intertwined with the study of Computer vision in a number of ways.
David E. Breen has included themes like Length scale, Data structure and Position in his Yarn study.
The concepts of his Finite element method study are interwoven with issues in Deformation, Kinematics and Stress.
His Biological system study integrates concerns from other disciplines, such as 3D reconstruction and Wing.
His Process research is multidisciplinary, incorporating elements of Algorithm, Level set method, Texture transfer and Level set.
Between 2016 and 2021, his most popular works were:
- On the role of material architecture in the mechanical behavior of knitted textiles (28 citations)
- Geodesy: Self-rising 2.5D Tiles by Printing along 2D Geodesic Closed Path (15 citations)
- An alternative reference space for H&E color normalization. (15 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Algorithm
David E. Breen spends much of his time researching Finite element method, Structural engineering, Yarn, Digital imaging and Artificial intelligence.
His Finite element method study incorporates themes from Flexural strength, Kinematics and Stress.
The Structural engineering study combines topics in areas such as Optimization problem, Software, Geometric modeling and Minimum function.
His work deals with themes such as Length scale, Deformation and Position, which intersect with Yarn.
The study incorporates disciplines such as Structure and Representation in addition to Digital imaging.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Computer vision and Pattern recognition.
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