H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 43 Citations 9,021 111 World Ranking 3915 National Ranking 1995

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Geometry

The scientist’s investigation covers issues in Artificial intelligence, Curvature, Geometry, Computer vision and Pattern recognition. Benjamin B. Kimia has researched Artificial intelligence in several fields, including Algorithm and Conservation law. His Curvature study integrates concerns from other disciplines, such as Smoothing, Dynamic programming and Mathematical analysis, Hamilton–Jacobi equation.

His research integrates issues of Cortical bone and Wrist in his study of Computer vision. While the research belongs to areas of Pattern recognition, he spends his time largely on the problem of Similarity, intersecting his research to questions surrounding Family of curves. His biological study spans a wide range of topics, including Robustness and Graph.

His most cited work include:

  • Recognition of shapes by editing their shock graphs (666 citations)
  • Shapes, shocks, and deformations I: the components of two-dimensional shape and the reaction-diffusion space (512 citations)
  • On aligning curves (353 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of investigation include Artificial intelligence, Computer vision, Algorithm, Geometry and Medial axis. The study of Artificial intelligence is intertwined with the study of Pattern recognition in a number of ways. In his work, Active shape model is strongly intertwined with Shape analysis, which is a subfield of Algorithm.

His Geometry research is multidisciplinary, incorporating perspectives in Boundary and Mathematical analysis. In Medial axis, Benjamin B. Kimia works on issues like Computational geometry, which are connected to Point. The concepts of his Curvature study are interwoven with issues in Smoothing, Dynamic programming and Tangent.

He most often published in these fields:

  • Artificial intelligence (58.06%)
  • Computer vision (40.65%)
  • Algorithm (21.29%)

What were the highlights of his more recent work (between 2013-2020)?

  • Artificial intelligence (58.06%)
  • Computer vision (40.65%)
  • Algorithm (21.29%)

In recent papers he was focusing on the following fields of study:

The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Algorithm, Pattern recognition and Point cloud. Artificial intelligence connects with themes related to Measure in his study. His studies deal with areas such as Precision and recall, Deep learning, Differential geometry and Pose as well as Algorithm.

His Differential geometry study combines topics from a wide range of disciplines, such as Detector, Tangent, Edge detection, Histogram and Curvature. The Pattern recognition study combines topics in areas such as Object and Categorization. His work in Point cloud addresses subjects such as Polygon mesh, which are connected to disciplines such as Robotics.

Between 2013 and 2020, his most popular works were:

  • Navigation methods and apparatus for the visually impaired (28 citations)
  • Multiview Differential Geometry of Curves (16 citations)
  • From Multiview Image Curves to 3D Drawings (12 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Computer vision
  • Geometry

Benjamin B. Kimia focuses on Artificial intelligence, Image, Curvature, Algorithm and Differential geometry. His Artificial intelligence research includes themes of Polygon mesh and Pattern recognition. His Pattern recognition research incorporates themes from Stability, Measure, Point and Noise.

Image is a subfield of Computer vision that he studies. He combines subjects such as Image segmentation, Detector, Precision and recall, Edge detection and Histogram with his study of Curvature. His Algorithm study combines topics in areas such as Epipolar geometry, Projective geometry, Algebraic curve and Tangent.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Recognition of shapes by editing their shock graphs

T.B. Sebastian;P.N. Klein;B.B. Kimia.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2004)

928 Citations

Shapes, shocks, and deformations I: the components of two-dimensional shape and the reaction-diffusion space

Benjamin B. Kimia;Allen R. Tannenbaum;Steven W. Zucker.
International Journal of Computer Vision (1995)

833 Citations

On aligning curves

T.B. Sebastian;P.N. Klein;B.B. Kimia.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2003)

491 Citations

Recognition of Shapes by Editing Shock Graphs

Thomas B. Sebastian;Philip N. Klein;Benjamin B. Kimia;Providence Ri.
international conference on computer vision (2001)

428 Citations

Symmetry-Based Indexing of Image Databases

Daniel Sharvit;Jacky Chan;Hüseyin Tek;Benjamin B. Kimia.
Journal of Visual Communication and Image Representation (1998)

406 Citations

3D object recognition using shape similiarity-based aspect graph

C.M. Cyr;B.B. Kimia.
international conference on computer vision (2001)

342 Citations

Parts of visual form: computational aspects

K. Siddiqi;B.B. Kimia.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1995)

322 Citations

On the evolution of curves via a function of curvature. I. The classical case

Benjamin B Kimia;Allen Tannenbaum;Allen Tannenbaum;Steven W Zucker.
Journal of Mathematical Analysis and Applications (1992)

256 Citations

Toward a computational theory of shape: an overview

B. B. Kimia;A. Tannenbaum;S. W. Zucker.
european conference on computer vision (1990)

236 Citations

A shock grammar for recognition

K. Siddiqi;B.B. Kimia.
computer vision and pattern recognition (1996)

228 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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