What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Geometry
- Algorithm
Bianca Falcidieno mainly focuses on Polygon mesh, Topology, Surface, Discrete mathematics and Feature.
Her Polygon mesh study is related to the wider topic of Geometry.
Her Topology study combines topics from a wide range of disciplines, such as Bowyer–Watson algorithm, Constrained Delaunay triangulation and Discrete geometry.
The subject of her Feature research is within the realm of Artificial intelligence.
Her research investigates the link between Adjacency list and topics such as Face that cross with problems in Theoretical computer science, Binary tree, Metric and Algorithm.
Her work carried out in the field of Reeb graph brings together such families of science as Shape analysis, Graph and Graphics.
Her most cited work include:
- Hierarchical mesh segmentation based on fitting primitives (358 citations)
- Reeb graphs for shape analysis and applications (208 citations)
- Describing shapes by geometrical-topological properties of real functions (187 citations)
What are the main themes of her work throughout her whole career to date?
Bianca Falcidieno focuses on Artificial intelligence, Polygon mesh, Pattern recognition, Shape analysis and Theoretical computer science.
Her studies deal with areas such as Machine learning and Computer vision as well as Artificial intelligence.
The various areas that she examines in her Polygon mesh study include Algorithm and Mesh generation.
Many of her studies on Algorithm involve topics that are commonly interrelated, such as Set.
She interconnects Active shape model and Reeb graph, Topology in the investigation of issues within Shape analysis.
Her research integrates issues of CAD and Finite element method in her study of Theoretical computer science.
She most often published in these fields:
- Artificial intelligence (27.08%)
- Polygon mesh (15.10%)
- Pattern recognition (12.50%)
What were the highlights of her more recent work (between 2010-2021)?
- Artificial intelligence (27.08%)
- Pattern recognition (12.50%)
- Shape analysis (12.50%)
In recent papers she was focusing on the following fields of study:
Bianca Falcidieno mostly deals with Artificial intelligence, Pattern recognition, Shape analysis, Polygon mesh and Hough transform.
In her study, which falls under the umbrella issue of Artificial intelligence, Curvature is strongly linked to Computer vision.
Her Pattern recognition research is multidisciplinary, relying on both 3d shapes, Computing Methodologies and Feature.
Her studies in Shape analysis integrate themes in fields like Scale-invariant feature transform, 3d surfaces, Active shape model, Algorithm and Differential geometry.
Her Polygon mesh research includes themes of Discrete mathematics and Point cloud.
Her research on Hough transform also deals with topics like
- Algebraic curve, which have a strong connection to Surface and Feature extraction,
- Representation which is related to area like Curvilinear coordinates, Bézier curve, Polynomial and Triangle mesh.
Between 2010 and 2021, her most popular works were:
- Semantic 3D Media and Content: Semantics and 3D media: Current issues and perspectives (31 citations)
- Graph-based representations of point clouds (31 citations)
- Recognition of feature curves on 3D shapes using an algebraic approach to Hough transforms (25 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- Geometry
- Algorithm
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Shape analysis, Theoretical computer science and Differential geometry.
Her Artificial intelligence study frequently intersects with other fields, such as Stability.
The concepts of her Pattern recognition study are interwoven with issues in Polygon mesh, Computer graphics and 3d model.
Her research in Shape analysis intersects with topics in Scale-invariant feature transform, 3d surfaces, Active shape model, Cluster analysis and Scalar.
Her Theoretical computer science research incorporates themes from Lattice graph, Geometric graph theory, Graph property and Strength of a graph.
Her Differential geometry research integrates issues from Geometry and topology, Computational topology, Topological space and Algorithm.
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