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Masanori Nakayama
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2020 – today
- 2023
- [j5]Akinori Ishitobi
, Masanori Nakayama, Issei Fujishiro:
Visual simulation of crack and bend generation in deteriorated films coated on metal objects: Combination of static fracture and position-based deformation. Vis. Comput. 39(8): 3403-3415 (2023) - [j4]Masanori Nakayama
HYDRO: Optimizing interactive hybrid images for digital signage content. Virtual Real. Intell. Hardw. 5(6): 565-577 (2023) - 2021
- [j3]Fatemeh Mirzapour-Shafiyi
Numerical evaluation reveals the effect of branching morphology on vessel transport properties during angiogenesis. PLoS Comput. Biol. 17(6) (2021) - [c7]Yume Asayama, Baoqing Wang, Masanori Nakayama, Hideki Shohjoh, Noboru Adachi, Yasushi Kiyoki, Issei Fujishiro:
THEMIS: Context-Sensitive Similarity Analysis for Wound Imagery Using Mathematical Model of Meaning. CW 2021: 129-132 - 2020
- [j2]Atsushi Miyazawa, Masanori Nakayama, Issei Fujishiro:
An Immersive Virtual Environment for Visualization of Complex and/or Infinitely Distant Territory. Trans. Comput. Sci. 36: 64-78 (2020) - [j1]Akinori Ishitobi, Masanori Nakayama, Issei Fujishiro:
Visual simulation of weathering coated metallic objects. Vis. Comput. 36(10): 2383-2393 (2020) - [c6]Ruizhe Li, Masanori Nakayama, Issei Fujishiro:
Automatic Generation of 3D Natural Anime-like Non-Player Characters with Machine Learning. CW 2020: 110-116
2010 – 2019
- 2019
- [c5]Akinori Ishitobi, Masanori Nakayama, Issei Fujishiro:
A Deformation Method for Simulating Coating Degradation While Taking Mechanical Behavior into Account. CW 2019: 360-361 - 2018
- [c4]Atsushi Miyazawa, Masanori Nakayama, Issei Fujishiro:
A Figurative and Non-topological Approach to Mathematical Visualization. CW 2018: 150-155 - [c3]Naoko Sawada, Masanori Nakayama, Makoto Uemura
TimeTubes: Automatic Extraction of Observable Blazar Features from Long-Term, Multi-Dimensional Datasets. SciVis 2018: 67-71 - 2017
- [c2]Naoko Sawada, Masanori Nakayama, Hsiang-Yun Wu, Makoto Uemura
TimeTubes: visual fusion and validation for ameliorating uncertainties of blazar datasets from different observatories. CGI 2017: 14:1-14:6 - 2015
- [c1]Issei Fujishiro, Naoki Haga, Masanori Nakayama:
SeeGroove: Supporting Groove Learning through Visualization. CW 2015: 189-192
Coauthor Index
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