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This graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
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A word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Bourquin, C., Porée, J., Rauby, B., Perrot, V. G., Ghigo, N., Belgharbi, H., Bélanger, S., Ramos-Palacios, G., Cortes, N., Ladret, H., Ikan, L., Casanova, C., Lesage, F., & Provost, J. (2024). Quantitative pulsatility measurements using 3D dynamic ultrasound localization microscopy. Physics in Medicine and Biology, 69(4), 045017 (14 pages). Available
Kantor, C., Boussioux, L., Rauby, B., & Talbot, H. (2021, February). Gradient-Based Localization and Spatial Attention for Confidence Measure in Fine-Grained Recognition using Deep Neural Networks [Paper]. 35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence. External link
Kantor, C., Rauby, B., Boussioux, L., Jehanno, E., Picard, A.-P. D., Larrivee, M., & Talbot, H. (2020, November). Asymptotic cross-entropy weighting and guided-loss in supervised hierarchical setting using deep attention networks [Paper]. AAAI Fall Symposium on AI for Social Good, (AI4SG 2020). Unavailable
Leconte, A., Porée, J., Rauby, B., Wu, A., Ghigo, N., Xing, P., Lee, S., Bourquin, C., Ramos-Palacios, G., Sadikot, A. F., & Provost, J. (2024). A Tracking prior to Localization workflow for Ultrasound Localization Microscopy. IEEE Transactions on Medical Imaging, 1-1. External link
Leconte, A., Porée, J., Rauby, B., Xing, P., Bourquin, C., Ghigo, N., Ramos, G. P., Sadikot, A. F., & Provost, J. (2023). Direct spatiotemporal localization of microbubble trajectories for highly resolved hemodynamics in ultrasound localization microscopy. The Journal of the Acoustical Society of America, 153(3_suppleme), A29-A29. External link
Rauby, B., Xing, P., Gasse, M., & Provost, J. (2024). Deep learning in ultrasound localization microscopy : applications and perspectives. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 3462299 (23 pages). Available
Xing, P., Porée, J., Rauby, B., Malescot, A., Martineau, E., Perrot, V., Rungta, R. L., & Provost, J. (2023). Phase Aberration Correction for in vivo Ultrasound Localization Microscopy Using a Spatiotemporal Complex-Valued Neural Network. IEEE Transactions on Medical Imaging, 12 pages. External link