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 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.
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.
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.
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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)
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)
On aligning curves
T.B. Sebastian;P.N. Klein;B.B. Kimia.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2003)
Recognition of Shapes by Editing Shock Graphs
Thomas B. Sebastian;Philip N. Klein;Benjamin B. Kimia;Providence Ri.
international conference on computer vision (2001)
Symmetry-Based Indexing of Image Databases
Daniel Sharvit;Jacky Chan;Hüseyin Tek;Benjamin B. Kimia.
Journal of Visual Communication and Image Representation (1998)
3D object recognition using shape similiarity-based aspect graph
C.M. Cyr;B.B. Kimia.
international conference on computer vision (2001)
Parts of visual form: computational aspects
K. Siddiqi;B.B. Kimia.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1995)
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)
Toward a computational theory of shape: an overview
B. B. Kimia;A. Tannenbaum;S. W. Zucker.
european conference on computer vision (1990)
A shock grammar for recognition
K. Siddiqi;B.B. Kimia.
computer vision and pattern recognition (1996)
Profile was last updated on December 6th, 2021.
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