167 citations
- The University of TokyoJP47 papers
- National Astronomical Observatory of JapanJP30 papers
- Kyoto UniversityJP23 papers
- Astrobiology CenterJP15 papers
- Kagoshima UniversityJP13 papers
- National Institute of InformaticsJP11 papers
- The Graduate University for Advanced Studies, SOKENDAIJP11 papers
- Tohoku UniversityJP11 papers
- Ehime UniversityJP10 papers
- Japan Science and Technology AgencyJP10 papers
- Nagoya UniversityJP10 papers
- University of Maryland, College ParkUS9 papers
8 papers · 1 filter
Japanese Tort-case Dataset for Rationale-supported Legal Judgment Prediction
Hiroaki Yamada, Takenobu Tokunaga, Ryutaro Ohara +3
This paper presents the first dataset for Japanese Legal Judgment Prediction (LJP), the Japanese Tort-case Dataset (JTD), which features two tasks: tort prediction and its rational…
Choquet integrals, Hausdorff content and fractional operators
Naoya Hatano, Ryota Kawasumi, Hiroki Saito +1
It is shown that the fractional integral operator , , and the fractional maximal operator , , are bounded on weak Choquet spaces with respect to Hausdorff…
Characterizing Data Assimilation in Navier-Stokes Turbulence with Transverse Lyapunov Exponents
Masanobu Inubushi, Yoshitaka Saiki, Miki U. Kobayashi +1
Data assimilation (DA) reconstructing small-scale turbulent structures is crucial for forecasting and understanding turbulence. This study proposes a theoretical framework for DA b…
Learning Self-Prior for Mesh Inpainting Using Self-Supervised Graph Convolutional Networks
Shota Hattori, Tatsuya Yatagawa, Yutaka Ohtake +1
In this paper, we present a self-prior-based mesh inpainting framework that requires only an incomplete mesh as input, without the need for any training datasets. Additionally, our…
Event-based Camera Simulation using Monte Carlo Path Tracing with Adaptive Denoising
Yuta Tsuji, Tatsuya Yatagawa, Hiroyuki Kubo +1
This paper presents an algorithm to obtain an event-based video from noisy frames given by physics-based Monte Carlo path tracing over a synthetic 3D scene. Given the nature of dyn…
Toward Extremely Lightweight Distracted Driver Recognition With Distillation-Based Neural Architecture Search and Knowledge Transfer
Dichao Liu, Toshihiko Yamasaki, Yu Wang +2
The number of traffic accidents has been continuously increasing in recent years worldwide. Many accidents are caused by distracted drivers, who take their attention away from driv…