Yukiko Kenmochi⋆

916 total citations
32 papers, 188 citations indexed

About

Yukiko Kenmochi⋆ is a scholar working on Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Computational Mechanics. According to data from OpenAlex, Yukiko Kenmochi⋆ has authored 32 papers receiving a total of 188 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Computer Vision and Pattern Recognition, 8 papers in Computational Theory and Mathematics and 5 papers in Computational Mechanics. Recurrent topics in Yukiko Kenmochi⋆'s work include Medical Image Segmentation Techniques (24 papers), Digital Image Processing Techniques (23 papers) and Image Retrieval and Classification Techniques (7 papers). Yukiko Kenmochi⋆ is often cited by papers focused on Medical Image Segmentation Techniques (24 papers), Digital Image Processing Techniques (23 papers) and Image Retrieval and Classification Techniques (7 papers). Yukiko Kenmochi⋆ collaborates with scholars based in France, Japan and Brazil. Yukiko Kenmochi⋆'s co-authors include Silvio Jamil F. Guimarães, Jean Cousty, Laurent Najman, Nicolas Passat, Atsushi Imiya, Akira Ichikawa, Reinhard Klette, Hugues Talbot, Akihiro Sugimoto and Benjamin Perret and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Image Processing and Pattern Recognition.

In The Last Decade

Yukiko Kenmochi⋆

25 papers receiving 180 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yukiko Kenmochi⋆ France 9 159 33 21 19 16 32 188
E. S. Deutsch United States 5 290 1.8× 20 0.6× 30 1.4× 14 0.7× 16 1.0× 9 333
Siddharth Manay United States 3 154 1.0× 7 0.2× 9 0.4× 40 2.1× 21 1.3× 6 199
Laura Papaleo Italy 8 134 0.8× 87 2.6× 49 2.3× 59 3.1× 18 1.1× 24 244
Alexander W. Bergman United States 5 79 0.5× 6 0.2× 42 2.0× 30 1.6× 7 0.4× 6 114
Lanqing Guo Singapore 10 261 1.6× 8 0.2× 8 0.4× 11 0.6× 35 2.2× 28 346
Éric Andrès France 7 172 1.1× 45 1.4× 78 3.7× 49 2.6× 8 0.5× 28 209
A.-R. Mansouri Canada 10 366 2.3× 7 0.2× 20 1.0× 37 1.9× 22 1.4× 25 404
Marcelo Bernardes Vieira Brazil 8 140 0.9× 4 0.1× 19 0.9× 18 0.9× 45 2.8× 52 187
Kenneth Weiss United States 9 86 0.5× 64 1.9× 84 4.0× 41 2.2× 3 0.2× 26 162
Andrey Voynov Russia 7 97 0.6× 47 1.4× 32 1.5× 15 0.8× 22 1.4× 14 200

Countries citing papers authored by Yukiko Kenmochi⋆

Since Specialization
Citations

This map shows the geographic impact of Yukiko Kenmochi⋆'s research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yukiko Kenmochi⋆ with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yukiko Kenmochi⋆ more than expected).

Fields of papers citing papers by Yukiko Kenmochi⋆

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yukiko Kenmochi⋆. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yukiko Kenmochi⋆. The network helps show where Yukiko Kenmochi⋆ may publish in the future.

Co-authorship network of co-authors of Yukiko Kenmochi⋆

This figure shows the co-authorship network connecting the top 25 collaborators of Yukiko Kenmochi⋆. A scholar is included among the top collaborators of Yukiko Kenmochi⋆ based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yukiko Kenmochi⋆. Yukiko Kenmochi⋆ is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Passat, Nicolas, et al.. (2023). Morphological Hierarchies: A Unifying Framework with New Trees. Journal of Mathematical Imaging and Vision. 65(5). 718–753.
2.
Passat, Nicolas, et al.. (2022). Homotopic Affine Transformations in the 2D Cartesian Grid. Journal of Mathematical Imaging and Vision. 64(7). 786–806.
3.
Perret, Benjamin, Jean Cousty, Silvio Jamil F. Guimarães, Yukiko Kenmochi⋆, & Laurent Najman. (2019). Removing non-significant regions in hierarchical clustering and segmentation. Pattern Recognition Letters. 128. 433–439. 8 indexed citations
4.
Perret, Benjamin, Giovanni Chierchia, Jean Cousty, et al.. (2019). Higra: Hierarchical Graph Analysis. SoftwareX. 10. 100335–100335. 19 indexed citations
5.
Cousty, Jean, et al.. (2019). Hierarchical segmentation from a non-increasing edge observation attribute. Pattern Recognition Letters. 131. 105–112. 2 indexed citations
6.
Cœurjolly, David, et al.. (2018). Characterization of Bijective Digitized Rotations on the Hexagonal Grid. Journal of Mathematical Imaging and Vision. 60(5). 707–716. 3 indexed citations
7.
Cousty, Jean, Laurent Najman, Yukiko Kenmochi⋆, & Silvio Jamil F. Guimarães. (2017). Hierarchical Segmentations with Graphs: Quasi-flat Zones, Minimum Spanning Trees, and Saliency Maps. Journal of Mathematical Imaging and Vision. 60(4). 479–502. 30 indexed citations
8.
Romon, Pascal, et al.. (2017). Bijective Digitized Rigid Motions on Subsets of the Plane. Journal of Mathematical Imaging and Vision. 59(1). 84–105. 13 indexed citations
9.
Kenmochi⋆, Yukiko, et al.. (2016). Discrete rigid registration: A local graph-search approach. Discrete Applied Mathematics. 216. 461–481. 2 indexed citations
10.
Kenmochi⋆, Yukiko, et al.. (2015). Volumetric relief map for intracranial cerebrospinal fluid distribution analysis. Computerized Medical Imaging and Graphics. 44. 26–40.
11.
Kenmochi⋆, Yukiko, et al.. (2013). Topology-Preserving Conditions for 2D Digital Images Under Rigid Transformations. Journal of Mathematical Imaging and Vision. 49(2). 418–433. 7 indexed citations
12.
Kenmochi⋆, Yukiko, et al.. (2012). Combinatorial structure of rigid transformations in 2D digital images. Computer Vision and Image Understanding. 117(4). 393–408. 10 indexed citations
13.
Sugimoto, Akihiro, et al.. (2010). 3D discrete rotations using hinge angles. Theoretical Computer Science. 412(15). 1378–1391. 1 indexed citations
14.
Kenmochi⋆, Yukiko, et al.. (2009). Computing upper and lower bounds of rotation angles from digital images. Pattern Recognition. 42(8). 1708–1717. 6 indexed citations
15.
Kenmochi⋆, Yukiko & Atsushi Imiya. (2006). Combinatorial boundary of a 3D lattice point set. Journal of Visual Communication and Image Representation. 17(4). 738–766. 4 indexed citations
16.
Kenmochi⋆, Yukiko, et al.. (2001). Fractal-based Image Disocclusion using Kernel Principal Components Analysis. 101(362). 55–62.
17.
Kenmochi⋆, Yukiko & Reinhard Klette. (2000). <title>Surface area estimation for digitized regular solids</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 4117. 100–111. 15 indexed citations
18.
Kenmochi⋆, Yukiko, Atsushi Imiya, & Akira Ichikawa. (1998). Boundary Extraction of Discrete Objects. Computer Vision and Image Understanding. 71(3). 281–293. 13 indexed citations
19.
Kenmochi⋆, Yukiko & Atsushi Imiya. (1998). <title>Discretization of three-dimensional objects: approximation and convergence</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 3454. 64–74. 1 indexed citations
20.
Kenmochi⋆, Yukiko, Atsushi Imiya, & Akira Ichikawa. (1997). Discrete combinatorial geometry. Pattern Recognition. 30(10). 1719–1728. 10 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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