What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Geometry
- Computer vision
Alla Sheffer spends much of her time researching Artificial intelligence, Polygon mesh, Computer vision, Mesh parameterization and Algorithm.
Her work on Machine learning expands to the thematically related Artificial intelligence.
The Geometry processing research Alla Sheffer does as part of her general Polygon mesh study is frequently linked to other disciplines of science, such as Deformation and Low distortion, therefore creating a link between diverse domains of science.
Her work on Orientation, Motion capture and Segmentation as part of general Computer vision study is frequently linked to Scale-space segmentation, bridging the gap between disciplines.
Her Mesh parameterization research incorporates themes from Flattening and Computer graphics.
Her Algorithm study integrates concerns from other disciplines, such as Feature and Morphing.
Her most cited work include:
- A scalable active framework for region annotation in 3D shape collections (428 citations)
- Mesh Parameterization Methods and Their Applications (356 citations)
- Cross-parameterization and compatible remeshing of 3D models (296 citations)
What are the main themes of her work throughout her whole career to date?
Artificial intelligence, Computer vision, Algorithm, Surface and Polygon mesh are her primary areas of study.
Alla Sheffer has researched Artificial intelligence in several fields, including Pattern recognition and Surface reconstruction.
Alla Sheffer interconnects Motion and Computer graphics in the investigation of issues within Computer vision.
The concepts of her Algorithm study are interwoven with issues in Range, Segmentation and Feature.
Her study on Surface also encompasses disciplines like
- Curvature that intertwine with fields like Sketch,
- Topology, which have a strong connection to Texture mapping and Mesh generation.
Her Polygon mesh study is concerned with Computer graphics in general.
She most often published in these fields:
- Artificial intelligence (29.08%)
- Computer vision (22.70%)
- Algorithm (19.15%)
What were the highlights of her more recent work (between 2017-2020)?
- Algorithm (19.15%)
- Artificial intelligence (29.08%)
- Surface (19.15%)
In recent papers she was focusing on the following fields of study:
Alla Sheffer focuses on Algorithm, Artificial intelligence, Surface, Computer vision and Polygon mesh.
Alla Sheffer usually deals with Algorithm and limits it to topics linked to Segmentation and Robustness.
Her Artificial intelligence research is multidisciplinary, relying on both Piecewise and Pattern recognition.
Her Surface research is multidisciplinary, incorporating perspectives in Tangent, Computation, Manifold and Virtual reality.
Her research integrates issues of Industrial design and Surface reconstruction in her study of Computer vision.
Her work carried out in the field of Polygon mesh brings together such families of science as Hexahedron and Feature.
Between 2017 and 2020, her most popular works were:
- Robust flow-guided neural prediction for sketch-based freeform surface modeling (23 citations)
- OptCuts: joint optimization of surface cuts and parameterization (18 citations)
- StrokeAggregator: consolidating raw sketches into artist-intended curve drawings (17 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- Geometry
- Computer vision
Alla Sheffer mostly deals with Engineering drawing, Sketch, Algorithm, Artificial intelligence and Artificial neural network.
Engineering drawing is connected with Sketch-based modeling, Fold and Gestalt psychology in her research.
Her Sketch study combines topics from a wide range of disciplines, such as Curvature, Convolutional neural network, Pattern recognition and Rendering.
Her research in Algorithm intersects with topics in Plane, Geometry processing, UV mapping and Mesh parameterization.
The various areas that she examines in her Artificial intelligence study include Polygon mesh and Surface reconstruction.
Her Artificial neural network research includes themes of Perspective, Orthographic projection and Computer vision.
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