J. Bobin

18.1k total citations
72 papers, 1.7k citations indexed

About

J. Bobin is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Astronomy and Astrophysics. According to data from OpenAlex, J. Bobin has authored 72 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Computer Vision and Pattern Recognition, 29 papers in Signal Processing and 22 papers in Astronomy and Astrophysics. Recurrent topics in J. Bobin's work include Image and Signal Denoising Methods (30 papers), Blind Source Separation Techniques (27 papers) and Sparse and Compressive Sensing Techniques (14 papers). J. Bobin is often cited by papers focused on Image and Signal Denoising Methods (30 papers), Blind Source Separation Techniques (27 papers) and Sparse and Compressive Sensing Techniques (14 papers). J. Bobin collaborates with scholars based in France, United States and Netherlands. J. Bobin's co-authors include Jean‐Luc Starck, Y. Moudden, Jalal Fadili, R. Ottensamer, David L. Donoho, Emmanuel J. Candès, Makhlad Chahid, Maxime Dahan, Vincent Studer and Hamed Mousavi and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Proceedings of the IEEE and Monthly Notices of the Royal Astronomical Society.

In The Last Decade

J. Bobin

67 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
J. Bobin France	18	604	471	370	346	269	72	1.7k
Christopher A. Metzler United States	17	449 0.7×	483 1.0×	511 1.4×	101 0.3×	354 1.3×	48	1.8k
Laurent Jacques Belgium	22	639 1.1×	783 1.7×	141 0.4×	313 0.9×	476 1.8×	115	1.8k
Timothy J. Schulz United States	16	831 1.4×	409 0.9×	69 0.2×	89 0.3×	698 2.6×	74	2.2k
Hongqiang Wang China	34	304 0.5×	434 0.9×	540 1.5×	319 0.9×	1.2k 4.5×	316	4.2k
Irad Yavneh Israel	27	363 0.6×	940 2.0×	200 0.5×	89 0.3×	220 0.8×	99	2.2k
Kyong Hwan Jin South Korea	14	747 1.2×	365 0.8×	84 0.2×	60 0.2×	997 3.7×	46	2.6k
Yongqiang Cheng China	29	213 0.4×	323 0.7×	470 1.3×	156 0.5×	853 3.2×	206	3.0k
Paul Rodríguez Peru	19	698 1.2×	337 0.7×	418 1.1×	118 0.3×	160 0.6×	115	1.6k
T. M. Cannon United States	14	402 0.7×	76 0.2×	110 0.3×	132 0.4×	238 0.9×	26	1.4k
Bruno Torrésani France	23	1.0k 1.7×	244 0.5×	61 0.2×	578 1.7×	166 0.6×	71	2.5k

Countries citing papers authored by J. Bobin

Since Specialization

Citations

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

Fields of papers citing papers by J. Bobin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. Bobin

This figure shows the co-authorship network connecting the top 25 collaborators of J. Bobin. A scholar is included among the top collaborators of J. Bobin 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 J. Bobin. J. Bobin 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

Castelli, E., Quentin Baghi, John G. Baker, et al.. (2025). Extracting gravitational wave signals from LISA data in the presence of artifacts. Classical and Quantum Gravity. 42(6). 65018–65018. 3 indexed citations

Bobin, J., et al.. (2025). Best of both worlds: Fusing hyperspectral data from two generations of spectro-imagers for X-ray astrophysics. Astronomy and Astrophysics. 694. A34–A34.

Bobin, J., et al.. (2024). SUSHI: An algorithm for source separation of hyperspectral images with non-stationary spectral variation. Astronomy and Astrophysics. 686. A259–A259. 1 indexed citations

Bobin, J., et al.. (2023). A hybrid Machine Learning unmixing method for automatic analysis of γ-spectra with spectral variability. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 1060. 169028–169028. 1 indexed citations

Mertens, Florent, J. Bobin, & Isabella P. Carucci. (2023). Retrieving the 21-cm signal from the Epoch of Reionization with learnt Gaussian process kernels. Monthly Notices of the Royal Astronomical Society. 527(2). 3517–3531. 13 indexed citations

Cunnington, Steven, Melis O Irfan, Isabella P. Carucci, Alkistis Pourtsidou, & J. Bobin. (2021). 21-cm foregrounds and polarization leakage: cleaning and mitigation strategies. Monthly Notices of the Royal Astronomical Society. 504(1). 208–227. 41 indexed citations

Bobin, Christophe, et al.. (2020). Metrological approach of γ -emitting radionuclides identification at low statistics: application of sparse spectral unmixing to scintillation detectors. Metrologia. 58(1). 15011–15011. 7 indexed citations

Moutarde, H., et al.. (2020). Sparsity-based recovery of Galactic-binary gravitational waves. Physical review. D. 102(10). 4 indexed citations

Bobin, J., et al.. (2020). Joint deconvolution and unsupervised source separation for data on the sphere. Digital Signal Processing. 110. 102946–102946. 2 indexed citations

10.

Bobin, J., et al.. (2018). Heuristics for Efficient Sparse Blind Source Separation. 489–493. 1 indexed citations

11.

Sureau, F., et al.. (2017). Unsupervised feature-learning for galaxy SEDs with denoising autoencoders. Springer Link (Chiba Institute of Technology). 13 indexed citations

12.

Rassat, A., Jean‐Luc Starck, P. Paykari, F. Sureau, & J. Bobin. (2014). Planck CMB Anomalies: Astrophysical and Cosmological Foregrounds and the Curse of Masking. arXiv (Cornell University). 1 indexed citations

13.

Starck, Jean‐Luc, et al.. (2013). iSAP: Interactive Sparse Astronomical Data Analysis Packages. Astrophysics Source Code Library. 2 indexed citations

14.

Bobin, J., Jean‐Luc Starck, F. Sureau, & S. Basak. (2013). Sparse component separation for accurate cosmic microwave background estimation. Springer Link (Chiba Institute of Technology). 35 indexed citations

15.

Bobin, J., Jean‐Luc Starck, F. Sureau, & Jalal Fadili. (2012). CMB Map Restoration. Advances in Astronomy. 2012. 1–15. 2 indexed citations

16.

Moudden, Y. & J. Bobin. (2010). Hyperspectral BSS Using GMCA With Spatio-Spectral Sparsity Constraints. IEEE Transactions on Image Processing. 20(3). 872–879. 12 indexed citations

17.

Bobin, J., Y. Moudden, Jean‐Luc Starck, & Jalal Fadili. (2009). Sparsity and morphological diversity for hyperspectral data analysis. 1481–1484. 2 indexed citations

18.

Bobin, J., Jean‐Luc Starck, Jalal Fadili, & Y. Moudden. (2007). Sparsity and Morphological Diversity in Blind Source Separation. IEEE Transactions on Image Processing. 16(11). 2662–2674. 133 indexed citations

19.

Bobin, J., Y. Moudden, Jean‐Luc Starck, Jalal Fadili, & N. Aghanim. (2007). SZ and CMB reconstruction using generalized morphological component analysis. Statistical Methodology. 5(4). 307–317. 38 indexed citations

20.

Starck, Jean‐Luc, Y. Moudden, J. Bobin, Michael Elad, & David L. Donoho. (2005). Morphological component analysis. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5914. 59140Q–59140Q. 82 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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