arXiv subjects

Koki Inoue

Publications and source records attributed to Koki Inoue.

4 recordsLinked to original sources

arXiv2026

OD-RASE: Ontology-Driven Risk Assessment and Safety Enhancement for Autonomous Driving

Although autonomous driving systems demonstrate high perception performance, they still face limitations when handling rare situations or complex road structures. Such road infrastructures are designed for human drivers, safety improvements are typically introduced only after accidents occur. This reactive approach poses a significant challenge for autonomous systems, which require proactive risk mitigation. To address this issue, we propose OD-RASE, a framework for enhancing the safety of autonomous driving systems by detecting road structures that cause traffic accidents and connecting these findings to infrastructure development. First, we formalize an ontology based on specialized domain knowledge of road traffic systems. In parallel, we generate infrastructure improvement proposals using a large-scale visual language model (LVLM) and use ontology-driven data filtering to enhance their reliability. This process automatically annotates improvement proposals on pre-accident road images, leading to the construction of a new dataset. Furthermore, we introduce the Baseline approach (OD-RASE model), which leverages LVLM and a diffusion model to produce both infrastructure improvement proposals and generated images of the improved road environment. Our experiments demonstrate that ontology-driven data filtering enables highly accurate prediction of accident-causing road structures and the corresponding improvement plans. We believe that this work contributes to the overall safety of traffic environments and marks an important step toward the broader adoption of autonomous driving systems.

cs.CV↗

arXiv2022

Dialogue system with humanoid robot

Today, as seen in smart speakers, spoken dialogue technology is rapidly advancing to enable human-like interaction. However, current dialogue systems cannot pay attention not only to the content of speech, but also to the way of speaking and eye contact and facial expressions, while watching the facial expressions of the person with whom one is speaking. Therefore, this study participated in a Japanese competition called the "Dialogue Robot Competition" and attempted to develop a dialogue system that includes control of not only the content of speech but also the robot's facial expressions and gaze in order to realize a humanoid robot that can naturally interact with humans.

cs.RO↗

arXiv2021

Wrinkle force microscopy: a new machine learning based approach to predict cell mechanics from images

Combining experiments with artificial intelligence algorithms, we propose a new machine learning based approach to extract the cellular force distributions from the microscope images. The full process can be divided into three steps. First, we culture the cells on a special substrate allowing to measure both the cellular traction force on the substrate and the corresponding substrate wrinkles simultaneously. The cellular forces are obtained using the traction force microscopy (TFM), at the same time that cell-generated contractile forces wrinkle their underlying substrate. Second, the wrinkle positions are extracted from the microscope images. Third, we train the machine learning system with GAN (generative adversarial network) by using sets of corresponding two images, the traction field and the input images (raw microscope images or extracted wrinkle images), as the training data. The network understands the way to convert the input images of the substrate wrinkles to the traction distribution from the training. After sufficient training, the network is utilized to predict the cellular forces just from the input images. Our system provides a powerful tool to evaluate the cellular forces efficiently because the forces can be predicted just by observing the cells under the microscope, which is a way simpler method compared to the TFM experiment. Additionally, the machine learning based approach presented here has the profound potential for being applied to diverse cellular assays for studying mechanobiology of cells.

physics.bio-ph↗

arXiv2018

Typical Purification Reproducing the Time Evolution of an Open Quantum System

It is known that an arbitrary quantum state can always be expressed in a pure state by preparing an appropriate ancilla system, which is called purification. The purification can always be performed when considering only a quantity not dependent on the quantum state of the ancilla system. Otherwise, the possibility of purification cannot be elucidated. In this study, we focus on the cases where a quantum system S and the ancilla system interact with each other, and investigate whether purification, which correctly reproduces the time evolution of the system S, is possible. Accordingly, when the ancilla system is a macrosystem, it can be shown that this purification is possible for a specific initial state.

cond-mat.stat-mech↗