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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.
Alsheghri, A., Ghadiri, F., Zhang, Y., Lessard, O., Keren, J., Cheriet, F., & Guibault, F. (2022, February). Semi-supervised segmentation of tooth from 3D scanned dental arches [Poster]. SPIE Medical Imaging 2022 : Image processing, San Diego, California, USA (6 pages). External link
Beckham, C., Honari, S., Lamb, A., Verma, V., Ghadiri, F., Hjelm, R. D., & Pal, C. J. (2019, May). Adversarial mixup resynthesizers [Paper]. Deep Generative Models for Highly Structured Data (DGS@ICLR 2019 Workshop), New Orleans, LA (20 pages). External link
Beckham, C., Honari, S., Verma, V., Lamb, A., Ghadiri, F., Hjelm, R. D., Bengio, Y., & Pal, C. J. (2019, December). On adversarial mixup resynthesis [Paper]. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada. External link
Ghadiri, F., Bergevin, R., & Bilodeau, G.-A. (2019). From superpixel to human shape modelling for carried object detection. Pattern Recognition, 89, 134-150. External link
Ghadiri, F., Bergevin, R., & Bilodeau, G.-A. (2017, September). Spatio-temporal consistency to detect and segment carried objects [Paper]. 28th British Machine Vision Conference, London, UK (12 pages). External link
Ghadiri, F., Bergevin, R., & Bilodeau, G.-A. (2016, October). Carried Object Detection Based on an Ensemble of Contour Exemplars [Paper]. 14th European Conference on Computer Vision (ECCV 2016), Amsterdam, The Netherlands. External link
Hosseinimanesh, G., Ghadiri, F., Guibault, F., Cheriet, F., & Keren, J. (2023, October). From Mesh Completion to AI Designed Crown [Paper]. 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023), Vancouver, BC, Canada. External link
Hosseinimanesh, G., Ghadiri, F., Alsheghri, A., Zhang, Y., Keren, J., Cheriet, F., & Guibault, F. (2023, February). Improving the quality of dental crown using a transformer-based method [Paper]. Medical Imaging 2023 : Physics of Medical Imaging,, San Diego, CA, USA (8 pages). External link