D-Index & Metrics Best Publications
Computer Science
France
2023

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 85 Citations 32,424 612 World Ranking 459 National Ranking 8

Research.com Recognitions

Awards & Achievements

2023 - Research.com Computer Science in France Leader Award

2022 - Research.com Computer Science in France Leader Award

2012 - IEEE Fellow For contributions to data fusion and image processing for remote sensing

Overview

What is she best known for?

The fields of study Jocelyn Chanussot is best known for:

  • Remote sensing
  • Statistics
  • Machine learning

Her study on Mathematical analysis is mostly dedicated to connecting different topics, such as Inverse problem and Subspace topology. Her Inverse problem study frequently involves adjacent topics like Mathematical analysis. Her Artificial intelligence study frequently draws connections to adjacent fields such as Segmentation. Her study ties her expertise on Image segmentation together with the subject of Segmentation. She carries out multidisciplinary research, doing studies in Hyperspectral imaging and Full spectral imaging. She carries out multidisciplinary research, doing studies in Full spectral imaging and Hyperspectral imaging. By researching both Remote sensing and Spatial analysis, she produces research that crosses academic boundaries. Her work often combines Spatial analysis and Remote sensing studies. Her Pattern recognition (psychology) study frequently links to adjacent areas such as Artificial intelligence.

Her most cited work include:

  • Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches (2083 citations)
  • Hyperspectral Remote Sensing Data Analysis and Future Challenges (1358 citations)
  • Advances in Spectral-Spatial Classification of Hyperspectral Images (1037 citations)

What are the main themes of her work throughout her whole career to date

Jocelyn Chanussot conducted interdisciplinary study in her works that combined Artificial intelligence and Algorithm. In her study, she carries out multidisciplinary Algorithm and Artificial intelligence research. Jocelyn Chanussot connects Remote sensing with Hyperspectral imaging in her research. Jocelyn Chanussot undertakes interdisciplinary study in the fields of Hyperspectral imaging and Remote sensing through her works. Computer vision is closely attributed to Image resolution in her research. Image resolution is closely attributed to Computer vision in her study. Image (mathematics) is often connected to Contextual image classification in her work. Contextual image classification is frequently linked to Image (mathematics) in her study.

Jocelyn Chanussot most often published in these fields:

  • Artificial intelligence (80.00%)
  • Pattern recognition (psychology) (60.00%)
  • Remote sensing (45.45%)

What were the highlights of her more recent work (between 2014-2022)?

  • Artificial intelligence (100.00%)
  • Data science (66.67%)
  • Image (mathematics) (66.67%)

In recent works Jocelyn Chanussot was focusing on the following fields of study:

Her Image (mathematics) study falls within the topics of Noise (video) and Contextual image classification. Her Noise (video) study frequently draws connections to other fields, such as Image (mathematics). Artificial intelligence is frequently linked to Sensor fusion in her study. Data science and Machine learning are two areas of study in which she engages in interdisciplinary work. She merges many fields, such as Machine learning and Deep learning, in her writings. Pattern recognition (psychology) is frequently linked to Artificial intelligence in her study. World Wide Web connects with themes related to Multimodality in her study. Many of her studies involve connections with topics such as World Wide Web and Multimodality. She regularly links together related areas like Computer vision in her Filter (signal processing) studies.

Between 2014 and 2022, her most popular works were:

  • Challenges and Opportunities of Multimodality and Data Fusion in Remote Sensing (140 citations)
  • Hyperspectral Image Classification—Traditional to Deep Models: A Survey for Future Prospects (56 citations)
  • Curvelet Based Contrast Enhancement in Fluoroscopic Sequences (12 citations)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches

J. M. Bioucas-Dias;A. Plaza;N. Dobigeon;M. Parente.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2012)

2504 Citations

Recent Advances in Techniques for Hyperspectral Image Processing

Antonio Plaza;Jon Atli Benediktsson;Joseph W. Boardman;Jason Brazile.
Remote Sensing of Environment (2009)

1692 Citations

Hyperspectral Remote Sensing Data Analysis and Future Challenges

J. M. Bioucas-Dias;A. Plaza;G. Camps-Valls;P. Scheunders.
IEEE Geoscience and Remote Sensing Magazine (2013)

1548 Citations

Advances in Spectral-Spatial Classification of Hyperspectral Images

M. Fauvel;Y. Tarabalka;J. A. Benediktsson;J. Chanussot.
Proceedings of the IEEE (2013)

1254 Citations

Spectral and Spatial Classification of Hyperspectral Data Using SVMs and Morphological Profiles

M. Fauvel;J.A. Benediktsson;J. Chanussot;J.R. Sveinsson.
IEEE Transactions on Geoscience and Remote Sensing (2008)

1220 Citations

A Critical Comparison Among Pansharpening Algorithms

Gemine Vivone;Luciano Alparone;Jocelyn Chanussot;Mauro Dalla Mura.
IEEE Transactions on Geoscience and Remote Sensing (2015)

905 Citations

Comparison of Pansharpening Algorithms: Outcome of the 2006 GRS-S Data-Fusion Contest

L.. Alparone;L.. Wald;J.. Chanussot;C.. Thomas.
IEEE Transactions on Geoscience and Remote Sensing (2007)

838 Citations

Spectral–Spatial Classification of Hyperspectral Imagery Based on Partitional Clustering Techniques

Y. Tarabalka;J.A. Benediktsson;J. Chanussot.
IEEE Transactions on Geoscience and Remote Sensing (2009)

819 Citations

SVM- and MRF-Based Method for Accurate Classification of Hyperspectral Images

Y Tarabalka;M Fauvel;J Chanussot;J A Benediktsson.
IEEE Geoscience and Remote Sensing Letters (2010)

776 Citations

Segmentation and classification of hyperspectral images using watershed transformation

Y. Tarabalka;J. Chanussot;J. A. Benediktsson.
Pattern Recognition (2010)

652 Citations

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