Ryoma Yataka
- Email:
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Position:
Research / Technical Staff
Visiting Research Scientist -
Education:
M.Eng., University of Tsukuba, 2017 -
Research Areas:
Ryoma's Quick Links
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Biography
Ryoma Yataka received M.Eng. in Information Engineering from University of Tsukuba in 2017. Since 2017, he has worked for the Information Technology Research & Development center (ITC), Mitsubishi Electric Corporation, Kamakura, Kanagawa, Japan. He is currently a visiting Researcher with the MERL and is also currently pursuing a Ph.D. degree with the Department of Computer Science, University of Tsukuba, Japan. His current research interests include machine learning, geometric deep learning, computer vision, signal processing, and their applications to sensing.
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Other Publications
- , "Grassmann Manifold Flows for Stable Shape Generation", Advances in Neural Information Processing Systems, 2023.BibTeX
- @Inproceedings{Yataka2023_GrCNF,
- author = {Yataka, Ryoma and Hirashima, Kazuki and Shiraishi, Masashi},
- title = {Grassmann Manifold Flows for Stable Shape Generation},
- booktitle = {Advances in Neural Information Processing Systems},
- year = 2023
- }
- , "Multiple Hypothesis Tracking with Merged Bounding Box Measurements Considering Occlusion", IEICE Transactions on Information and Systems, Vol. E105.D, No. 8, pp. 1456-1463, 2022.BibTeX
- @Article{Yataka2022_OCTET,
- author = {YAMADA, Tetsutaro and GOCHO, Masato and AKAMA, Kei and YATAKA, Ryoma and KAMEDA, Hiroshi},
- title = {Multiple Hypothesis Tracking with Merged Bounding Box Measurements Considering Occlusion},
- journal = {IEICE Transactions on Information and Systems},
- year = 2022,
- volume = {E105.D},
- number = 8,
- pages = {1456--1463}
- }
- , "Unknown Object Recognition Using the Manifold Structure of Class Distributions", 2022 19th European Radar Conference (EuRAD), 2022, pp. 193-196.BibTeX
- @Inproceedings{Yataka2022_UOR,
- author = {Yataka, Ryoma and Shiraishi, Masashi},
- title = {Unknown Object Recognition Using the Manifold Structure of Class Distributions},
- booktitle = {2022 19th European Radar Conference (EuRAD)},
- year = 2022,
- pages = {193--196}
- }
- , "Projection Metric Learning of Updated-Subspaces for Radar Target Classification", 2019 16th European Radar Conference (EuRAD), 2019, pp. 5-8.BibTeX
- @Inproceedings{Yataka2019_PMLUS,
- author = {Yataka, Ryoma and Hirashima, Kazuki and Matsuda, Takafumi and Tanaka, Tai and Gocho, Masato and Shiraishi, Masashi},
- title = {Projection Metric Learning of Updated-Subspaces for Radar Target Classification},
- booktitle = {2019 16th European Radar Conference (EuRAD)},
- year = 2019,
- pages = {5--8}
- }
- , "Micro-Doppler Analysis under Various Aspect Angles for Small UAV Classification", 2019 IEEE Asia-Pacific Microwave Conference (APMC), 2019, pp. 102-104.BibTeX
- @Inproceedings{Yataka2019_UAVClassification,
- author = {Matsuda, Takafumi and Yataka, Ryoma and Gocho, Masato and Tanaka, Tai},
- title = {Micro-Doppler Analysis under Various Aspect Angles for Small UAV Classification},
- booktitle = {2019 IEEE Asia-Pacific Microwave Conference (APMC)},
- year = 2019,
- pages = {102--104}
- }
- , "Three-dimensional Object Recognition via Subspace Representation on a Grassmann Manifold", 2017, Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,.BibTeX
- @Conference{Yataka2017_GMSM,
- author = {Yataka, Ryoma and Fukui, Kazuhiro},
- title = {Three-dimensional Object Recognition via Subspace Representation on a Grassmann Manifold},
- booktitle = {Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
- year = 2017,
- pages = {208--216},
- organization = {INSTICC},
- publisher = {SciTePress}
- }
- , "Grassmann Manifold Flows for Stable Shape Generation", Advances in Neural Information Processing Systems, 2023.