Germain Forestier

8.3k total citations · 2 hit papers
83 papers, 3.9k citations indexed

About

Germain Forestier is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Germain Forestier has authored 83 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Artificial Intelligence, 29 papers in Signal Processing and 13 papers in Computer Vision and Pattern Recognition. Recurrent topics in Germain Forestier's work include Time Series Analysis and Forecasting (25 papers), Anomaly Detection Techniques and Applications (19 papers) and Remote-Sensing Image Classification (13 papers). Germain Forestier is often cited by papers focused on Time Series Analysis and Forecasting (25 papers), Anomaly Detection Techniques and Applications (19 papers) and Remote-Sensing Image Classification (13 papers). Germain Forestier collaborates with scholars based in France, Australia and Switzerland. Germain Forestier's co-authors include Jonathan Weber, Lhassane Idoumghar, Pierre-Alain Müller, Hassan Ismail Fawaz, Cédric Wemmert, Pierre Gançarski, François Petitjean, Pierre Jannin, Geoffrey I. Webb and Laurent Riffaud and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Germain Forestier

75 papers receiving 3.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep learning for time series classification: a review

2019 2.0k citations Hassan Ismail Fawaz, Germain Forestier et al. profile →
Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey

2024 80 citations Chang Wei Tan, Geoffrey I. Webb et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Germain Forestier France	24	1.8k	1.5k	633	472	320	83	3.9k
Jonathan Weber France	21	1.4k 0.8×	1.2k 0.8×	439 0.7×	296 0.6×	115 0.4×	67	3.4k
Lhassane Idoumghar France	18	1.4k 0.8×	1.1k 0.8×	427 0.7×	288 0.6×	106 0.3×	118	3.2k
Hassan Ismail Fawaz France	8	1.2k 0.7×	1.1k 0.8×	316 0.5×	272 0.6×	106 0.3×	10	2.5k
Pierre-Alain Müller France	14	1.3k 0.7×	1.1k 0.8×	318 0.5×	241 0.5×	69 0.2×	26	2.7k
Kemal Polat Türkiye	46	2.9k 1.6×	1.1k 0.8×	1.3k 2.1×	1.0k 2.2×	146 0.5×	239	7.9k
Lipo Wang Singapore	36	2.2k 1.2×	558 0.4×	1.4k 2.3×	505 1.1×	77 0.2×	185	6.8k
José Luis Rojo‐Álvarez Spain	29	587 0.3×	352 0.2×	357 0.6×	321 0.7×	158 0.5×	245	3.6k
Yudong Chen China	29	1.2k 0.7×	409 0.3×	1.0k 1.7×	232 0.5×	127 0.4×	143	4.5k
Hiroaki Sakoe Japan	14	2.0k 1.1×	2.3k 1.6×	1.4k 2.3×	384 0.8×	55 0.2×	47	5.1k
Tuan D. Pham Australia	33	1.2k 0.6×	432 0.3×	1.2k 1.9×	303 0.6×	101 0.3×	295	4.2k

Countries citing papers authored by Germain Forestier

Since Specialization

Citations

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

Fields of papers citing papers by Germain Forestier

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Germain Forestier

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

All Works

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20 of 20 papers shown

Devanne, Maxime, et al.. (2025). Establishing a unified evaluation framework for human motion generation: A comparative analysis of metrics. Computer Vision and Image Understanding. 254. 104337–104337.

Forestier, Germain, et al.. (2025). Automatic detection of in-stream river wood from random forest machine learning and exogenous indices using very high-resolution aerial imagery. Environmental Modelling & Software. 190. 106460–106460.

Bagnall, Anthony, Matthew Middlehurst, Germain Forestier, et al.. (2024). A Hands-on Introduction to Time Series Classification and Regression. ePrints Soton (University of Southampton). 6410–6411. 2 indexed citations

Hibert, Clément, Lise Retailleau, Jean‐Marie Saurel, et al.. (2024). Self-supervised learning of seismological data reveals new eruptive sequences at the Mayotte submarine volcano. Geophysical Journal International. 240(1). 1–12. 1 indexed citations

Fawaz, Hassan Ismail, Maxime Devanne, Jonathan Weber, et al.. (2023). Time series adversarial attacks: an investigation of smooth perturbations and defense approaches. International Journal of Data Science and Analytics. 19(1). 129–139. 2 indexed citations

Devanne, Maxime, et al.. (2023). Estimating time series averages from latent space of multi-tasking neural networks. Knowledge and Information Systems. 65(11). 4967–5004. 1 indexed citations

Devanne, Maxime, et al.. (2023). Correction: Estimating time series averages from latent space of multi-tasking neural networks. Knowledge and Information Systems. 66(2). 1521–1521. 1 indexed citations

Devanne, Maxime, Jonathan Weber, Caroline Truntzer, et al.. (2021). Deep learning for colon cancer histopathological images analysis. Computers in Biology and Medicine. 136. 104730–104730. 139 indexed citations

Schönmeyer, Ralf, Germain Forestier, Nicolas Brieu, et al.. (2020). Graph-based description of tertiary lymphoid organs at single-cell level. PLoS Computational Biology. 16(2). e1007385–e1007385. 7 indexed citations

10.

Pelaccia, Thierry, Germain Forestier, & Cédric Wemmert. (2020). Une intelligence artificielle raisonne-t-elle de la même façon que les cliniciens pour poser des diagnostics ?. La Revue de Médecine Interne. 41(3). 192–195. 3 indexed citations

11.

Fawaz, Hassan Ismail, Germain Forestier, Jonathan Weber, Lhassane Idoumghar, & Pierre-Alain Müller. (2019). Adversarial Attacks on Deep Neural Networks for Time Series Classification. arXiv (Cornell University). 1–8. 81 indexed citations

12.

Fawaz, Hassan Ismail, Germain Forestier, Jonathan Weber, Lhassane Idoumghar, & Pierre-Alain Müller. (2019). Accurate and interpretable evaluation of surgical skills from kinematic data using fully convolutional neural networks. univOAK (4 institutions : Université de Strasbourg, Université de Haute Alsace, INSA Strasbourg, Bibliothèque Nationale et Universitaire de Strasbourg). 77 indexed citations

13.

Grote, Anne, et al.. (2018). Crowdsourcing of Histological Image Labeling and Object Delineation by Medical Students. IEEE Transactions on Medical Imaging. 38(5). 1284–1294. 19 indexed citations

14.

Forestier, Germain, François Petitjean, Pavel Senin, et al.. (2018). Surgical motion analysis using discriminative interpretable patterns. Artificial Intelligence in Medicine. 91. 3–11. 46 indexed citations

15.

Alfonso, Juan Carlos López, Ralf Schönmeyer, Nicolas Brieu, et al.. (2016). In-silico insights on the prognostic potential of immune cell infiltration patterns in the breast lobular epithelium. Scientific Reports. 6(1). 33322–33322. 21 indexed citations

16.

Forestier, Germain, François Petitjean, Laurent Riffaud, & Pierre Jannin. (2014). Non-linear temporal scaling of surgical processes. Artificial Intelligence in Medicine. 62(3). 143–152. 5 indexed citations

17.

Gibaud, Bernard, Germain Forestier, Hugues Benoit-Cattin, et al.. (2014). OntoVIP: An ontology for the annotation of object models used for medical image simulation. Journal of Biomedical Informatics. 52. 279–292. 20 indexed citations

18.

Forestier, Germain, Florent Lalys, Laurent Riffaud, et al.. (2013). Multi-site study of surgical practice in neurosurgery based on surgical process models. Journal of Biomedical Informatics. 46(5). 822–829. 24 indexed citations

19.

Glatard, Tristan, Carole Lartizien, Bernard Gibaud, et al.. (2012). A Virtual Imaging Platform for Multi-Modality Medical Image Simulation. IEEE Transactions on Medical Imaging. 32(1). 110–118. 65 indexed citations

20.

Forestier, Germain, et al.. (2011). Classification of surgical processes using dynamic time warping. Journal of Biomedical Informatics. 45(2). 255–264. 62 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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