Joan Lasenby

6.2k citations
130 papers · 2.4k · 1 hit paper · h-index 25

Impact in

Papers in

Joan Lasenby

124 papers receiving 2.3k citations

Joan Lasenby's Hit Papers

Unsupervised Point Cloud Pre-training via Occlusion Completion 2021 · 144 citations
1440+1+3Years since publication4080120

Peers

Joan Lasenby
Comparison fields: 5 of 137
  • Human-Computer Interaction 199
  • Computer Vision and Pattern Recognition 722
  • Control and Systems Engineering 690
  • Geology 116
  • Applied Mathematics 194
Replace Ken Shoemake with:
Ken Shoemake United States
Ruzena Bajcsy United States
Shinji Umeyama Japan
Allen Y. Yang United States
Du Q. Huynh Australia
Xiaoji Niu China
Olivier Rioul France
Christoph Bregler United States
Panos Trahanias Greece
Kenichi Kanatani Japan
Joan Lasenby relative to Ken Shoemake United States Ken Shoemake's profile →
Citations per field
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Citations per year

Countries citing papers authored by Joan Lasenby

Since Specialization
Citations

This map shows the geographic impact of Joan Lasenby'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 Joan Lasenby with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joan Lasenby more than expected).

Fields of papers citing papers by Joan Lasenby

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joan Lasenby. 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 Joan Lasenby. The network helps show where Joan Lasenby may publish in the future.

Co-authors

The 25 scholars most cited alongside Joan Lasenby, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Joan Lasenby Line = papers co-authored together Joan Lasenby links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 130 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002290
2 2011264
3 2017146
4
Unsupervised Point Cloud Pre-training via Occlusion Completion
Hit paper breakdown →
2021144
5 199879
6 200273
7 202165
8 201260
9 201958
10 201351
11 202348
12
Inverse kinematics: a review of existing techniques and introduction of a new fast iterative solver
200947
13 200046
14 199946
15 199042
16 201541
17 201737
18 200334
19 201034
20 200834

About Joan Lasenby

Joan Lasenby is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering, Computational Mechanics, Applied Mathematics and Biomedical Engineering, having authored 130 papers that have together received 2.4k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (23 papers), Algebraic and Geometric Analysis (20 papers), Advanced Numerical Analysis Techniques (14 papers), Human Motion and Animation (13 papers), Mathematics and Applications (12 papers), Human Pose and Action Recognition (10 papers), Video Analysis and Summarization (9 papers) and Robotic Mechanisms and Dynamics (8 papers). The work is most often cited by research in Human-Computer Interaction (199 citations), Computer Vision and Pattern Recognition (722 citations), Control and Systems Engineering (690 citations), Geology (116 citations) and Applied Mathematics (194 citations). Joan Lasenby has collaborated with scholars based in United Kingdom, South Sudan and United States. Frequent co-authors include Andreas Aristidou, Sahan Gamage, Chris Doran, A. Lasenby, Yiorgos Chrysanthou, Duo Li, Adi Shamir, Jonathan Cameron, Quentin Paletta and Xiangyu Yue. Their work appears in journals such as Scientific Reports, Mathematical Methods in the Applied Sciences, Applied Energy, Journal of Biomechanics and Royal Society Open Science.

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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