François Petitjean
- Artificial Intelligence top 1%
- Signal Processing top 0.5%
- Ecology top 5%
- Computer Vision and Pattern Recognition top 5%
- Global and Planetary Change top 10%
- Co-authors
- Pierre GançarskiAlain KetterlinGeoffrey I. WebbJordi IngladaGermain ForestierHai Long NguyenHong CaoEamonn Keogh
- Topics
- Time Series Analysis and Forecasting (20 papers)Remote Sensing in Agriculture (10 papers)Remote-Sensing Image Classification (10 papers)
- Journals
- Water Resources ResearchIEEE Transactions on Geoscience and Remote SensingFrontiers in Immunology
- Partner nations
- AustraliaFranceUnited States
In The Last Decade
François Petitjean
56 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 173
- Artificial Intelligence 894
- Signal Processing 824
- Ecology 353
- Computer Vision and Pattern Recognition 221
- Global and Planetary Change 206
Countries citing papers authored by François Petitjean
This map shows the geographic impact of François Petitjean'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 François Petitjean with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites François Petitjean more than expected).
Fields of papers citing papers by François Petitjean
This network shows the impact of papers produced by François Petitjean. 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 François Petitjean. The network helps show where François Petitjean may publish in the future.
Co-authorship network of co-authors of François Petitjean
This figure shows the co-authorship network connecting the top 25 collaborators of François Petitjean. A scholar is included among the top collaborators of François Petitjean 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 François Petitjean. François Petitjean is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 16 | |
| 2 | 24 | |
| 3 | Monash University, UEA, UCR Time Series Regression Archive | 4 |
| 4 | Available, but not accessible? Investigating publishers' e-lending licensing practices. | 5 |
| 5 | 4 | |
| 6 | 46 | |
| 7 | 14 | |
| 8 | 0 | |
| 9 | 58 | |
| 10 | 8 | |
| 11 | 20 | |
| 12 | Characterizing concept driftbreakdown → | 300 |
| 13 | 24 | |
| 14 | 5 | |
| 15 | 94 | |
| 16 | 45 | |
| 17 | 9 | |
| 18 | 12 | |
| 19 | A global averaging method for dynamic time warping, with applications to clusteringbreakdown → | 703 |
| 20 | 25 |
About François Petitjean
François Petitjean is a scholar working on Signal Processing, Media Technology and Health Informatics, having authored 57 papers that have together received 2.4k indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (20 papers), Remote Sensing in Agriculture (10 papers) and Remote-Sensing Image Classification (10 papers). The work is most often cited by research in Signal Processing (824 citations), Artificial Intelligence (894 citations) and Media Technology (173 citations). François Petitjean has collaborated with scholars based in Australia, France and United States. Frequent co-authors include Pierre Gançarski, Alain Ketterlin, Geoffrey I. Webb, Jordi Inglada, Germain Forestier, Hai Long Nguyen, Hong Cao, Eamonn Keogh, Hoang Anh Dau and Chang Wei Tan. Their work appears in journals such as Water Resources Research, IEEE Transactions on Geoscience and Remote Sensing and Frontiers in Immunology.
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.