Michael Sapienza

464 total citations
10 papers, 165 citations indexed

About

Michael Sapienza is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering and Control and Systems Engineering. According to data from OpenAlex, Michael Sapienza has authored 10 papers receiving a total of 165 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 3 papers in Biomedical Engineering and 2 papers in Control and Systems Engineering. Recurrent topics in Michael Sapienza's work include Human Pose and Action Recognition (5 papers), Gait Recognition and Analysis (3 papers) and Advanced Vision and Imaging (2 papers). Michael Sapienza is often cited by papers focused on Human Pose and Action Recognition (5 papers), Gait Recognition and Analysis (3 papers) and Advanced Vision and Imaging (2 papers). Michael Sapienza collaborates with scholars based in United Kingdom, Malta and France. Michael Sapienza's co-authors include Philip H. S. Torr, Fabio Cuzzolin, Stuart Golodetz, Saumya Jetley, Marloes Franssen, Helen Dawes, Johnny Collett, Patrick Esser, Suman Saha and Kenneth P. Camilleri and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and Gait & Posture.

In The Last Decade

Michael Sapienza

9 papers receiving 164 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael Sapienza United Kingdom	7	116	43	37	19	18	10	165
Youze Xue China	7	199 1.7×	31 0.7×	70 1.9×	46 2.4×	13 0.7×	11	279
Laura Contin Italy	7	18 0.2×	94 2.2×	11 0.3×	109 5.7×	73 4.1×	10	203
Stefano Bertuletti Italy	6	17 0.1×	34 0.8×	7 0.2×	5 0.3×	25 1.4×	11	89
Rajeswari India	5	67 0.6×	16 0.4×	67 1.8×	4 0.2×		19	252
Caizi Li China	7	52 0.4×	35 0.8×	28 0.8×	37 1.9×		14	150
Oscar Perdómo Colombia	10	115 1.0×	63 1.5×	38 1.0×	2 0.1×	6 0.3×	39	372
Amitojdeep Singh Canada	7	199 1.7×	33 0.8×	61 1.6×		5 0.3×	9	396
Boah Kim South Korea	6	170 1.5×	79 1.8×	48 1.3×	3 0.2×		13	273
Dong Wook Ko South Korea	5	75 0.6×	23 0.5×	13 0.4×	1 0.1×	4 0.2×	6	114
Xiuchao Sui Singapore	5	165 1.4×	23 0.5×	57 1.5×	2 0.1×		7	265

Countries citing papers authored by Michael Sapienza

Since Specialization

Citations

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

Fields of papers citing papers by Michael Sapienza

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Sapienza

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Sapienza. A scholar is included among the top collaborators of Michael Sapienza 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 Michael Sapienza. Michael Sapienza is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

1.

de, Rodrigo, Anurag Arnab, Stuart Golodetz, Michael Sapienza, & Philip H. S. Torr. (2018). Deep Fully-Connected Part-Based Models for Human Pose Estimation. Oxford University Research Archive (ORA) (University of Oxford). 327–342. 8 indexed citations

2.

Cuzzolin, Fabio, Michael Sapienza, Patrick Esser, et al.. (2017). Metric learning for Parkinsonian identification from IMU gait measurements. Gait & Posture. 54. 127–132. 40 indexed citations

3.

Jetley, Saumya, Michael Sapienza, Stuart Golodetz, & Philip H. S. Torr. (2017). Straight to Shapes: Real-Time Detection of Encoded Shapes. 4207–4216. 27 indexed citations

4.

Golodetz, Stuart, Michael Sapienza, Vibhav Vineet, et al.. (2015). SemanticPaint. 1–1. 6 indexed citations

5.

Sapienza, Michael & Kenneth P. Camilleri. (2014). Fasthpe : a recipe for quick head pose estimation. OAR@UM (University of Malta). 6 indexed citations

6.

Sapienza, Michael, Fabio Cuzzolin, & Philip H. S. Torr. (2013). Learning Discriminative Space–Time Action Parts from Weakly Labelled Videos. International Journal of Computer Vision. 110(1). 30–47. 39 indexed citations

7.

Cuzzolin, Fabio & Michael Sapienza. (2013). Learning Pullback HMM Distances. IEEE Transactions on Pattern Analysis and Machine Intelligence. 36(7). 1483–1489. 6 indexed citations

8.

Sapienza, Michael, Fabio Cuzzolin, & Philip H. S. Torr. (2012). Learning discriminative space-time actions from weakly labelled videos. 123.1–123.12. 27 indexed citations

9.

Sapienza, Michael & Kenneth P. Camilleri. (2012). A Generative Traversability Model for Monocular Robot Self-guidance. OAR@UM (University of Malta). 177–184.

10.

Sapienza, Michael, Miles Hansard, & Radu Horaud. (2012). Real-time visuomotor update of an active binocular head. Autonomous Robots. 34(1-2). 35–45. 6 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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