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Collaboration networkThis 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.
Use the mouse wheel or scroll gestures to zoom into the graph.
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Hold down the "Ctrl" key or the "⌘" key while clicking on the nodes to open the list of this person's publications.
Word cloudA 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.
Askari Hemmat, M., Savaria, Y., David, J. P., Honari, S., Perone, C. S., Rouhier, L., & Cohen-Adad, J. (2019, October). U-Net Fixed-Point Quantization for Medical Image Segmentation [Paper]. 22nd International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI 2019), Shenzhen, China. External link
Askari Hemmat, M., Honari, S., Rouhier, L., Perone, C. S., Cohen-Adad, J., Savaria, Y., & David, J. P. (2019, October). U-net fixed-point quantization for medical image segmentation [Paper]. 1st International Workshop on Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention (HAL-MICCAI 2019), Shenzhen, China. External link
Beckham, C., Weiss, M., Golemo, F., Honari, S., Nowrouzezahrai, D., & Pal, C. J. (2023). Visual question answering from another perspective: CLEVR mental rotation tests *. Pattern Recognition, 136, 109209 (12 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
Honari, S., Molchanov, P., Tyree, S., Vincent, P., Pal, C. J., & Kautz, J. (2018, June). Improving Landmark Localization with Semi-Supervised Learning [Paper]. 31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2018), Salt Lake City, UT, United states. External link
Honari, S., Yosinski, J., Vincent, P., & Pal, C. J. (2016, June). Recombinator networks: Learning coarse-to-fine feature aggregation [Paper]. IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), Las Vegas, NV, United states. External link
Moniz, J. R. A., Beckham, C., Rajotte, S., Honari, S., & Pal, C. J. (2018, December). Unsupervised depth estimation, 3D face rotation and replacement [Paper]. 32nd Conference on Neural Information Processing Systems (NIPS 2018), Montréal, Canada (11 pages). External link
Rim, D., Honari, S., Hasan, M. K., & Pal, C. J. (2015). Improving facial analysis and performance driven animation through disentangling identity and expression. Image and Vision Computing, 52, 125-140. External link
