Osaka University

research

∙ 12/12/2019

IterNet: Retinal Image Segmentation Utilizing Structural Redundancy in Vessel Networks

Retinal vessel segmentation is of great interest for diagnosis of retina...

Liangzhi Li, et al. ∙

research

∙ 04/15/2020

lamBERT: Language and Action Learning Using Multimodal BERT

Recently, the bidirectional encoder representations from transformers (B...

Kazuki Miyazawa, et al. ∙

research

∙ 10/04/2019

Motion Planning through Demonstration to Deal with Complex Motions in Assembly Process

Complex and skillful motions in actual assembly process are challenging ...

Yan Wang, et al. ∙

research

∙ 07/16/2019

Model-free Control of Chaos with Continuous Deep Q-learning

The OGY method is one of control methods for a chaotic system. In the me...

Junya Ikemoto, et al. ∙

research

∙ 01/21/2022

Deep reinforcement learning under signal temporal logic constraints using Lagrangian relaxation

Deep reinforcement learning (DRL) has attracted much attention as an app...

Junya Ikemoto, et al. ∙

research

∙ 04/26/2022

Multi-task Learning for Concurrent Prediction of Thermal Comfort, Sensation, and Preference

Indoor thermal comfort immensely impacts the health and performance of o...

Betty Lala, et al. ∙

research

∙ 12/23/2019

5D Light Field Synthesis from a Monocular Video

Commercially available light field cameras have difficulty in capturing ...

Kyuho Bae, et al. ∙

research

∙ 11/29/2018

Shape-conditioned Image Generation by Learning Latent Appearance Representation from Unpaired Data

Conditional image generation is effective for diverse tasks including tr...

Yutaro Miyauchi, et al. ∙

research

∙ 08/03/2021

Deep Reinforcement Learning Based Networked Control with Network Delays for Signal Temporal Logic Specifications

We present a novel deep reinforcement learning (DRL)-based design of a n...

Junya Ikemoto, et al. ∙

research

∙ 08/23/2019

Image based cellular contractile force evaluation with small-world network inspired CNN: SW-UNet

We propose an image-based cellular contractile force evaluation method u...

Li Honghan, et al. ∙

research

∙ 05/27/2020

Joint Learning of Vessel Segmentation and Artery/Vein Classification with Post-processing

Retinal imaging serves as a valuable tool for diagnosis of various disea...

Liangzhi Li, et al. ∙

research

∙ 07/12/2018

Maximizing Invariant Data Perturbation with Stochastic Optimization

Feature attribution methods, or saliency maps, are one of the most popul...

Kouichi Ikeno, et al. ∙

research

∙ 10/15/2021

FedMe: Federated Learning via Model Exchange

Federated learning is a distributed machine learning method in which a s...

Koji Matsuda, et al. ∙

research

∙ 11/22/2017

Hypergraph p-Laplacian: A Differential Geometry View

The graph Laplacian plays key roles in information processing of relatio...

Shota Saito, et al. ∙

research

∙ 11/24/2017

MPIIGaze: Real-World Dataset and Deep Appearance-Based Gaze Estimation

Learning-based methods are believed to work well for unconstrained gaze ...

Xucong Zhang, et al. ∙

research

∙ 10/10/2017

On- and Off-Policy Monotonic Policy Improvement

Monotonic policy improvement and off-policy learning are two main desira...

Ryo Iwaki, et al. ∙

research

∙ 10/12/2017

Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition

Spectral decomposition of the Koopman operator is attracting attention a...

Naoya Takeishi, et al. ∙

research

∙ 08/28/2017

Efficient Decision Trees for Multi-class Support Vector Machines Using Entropy and Generalization Error Estimation

We propose new methods for Support Vector Machines (SVMs) using tree arc...

Pittipol Kantavat, et al. ∙

research

∙ 05/14/2017

Relaxation heuristics for the set multicover problem with generalized upper bound constraints

We consider an extension of the set covering problem (SCP) introducing (...

Shunji Umetani, et al. ∙

research

∙ 06/01/2017

Efficient learning with robust gradient descent

Minimizing the empirical risk is a popular training strategy, but for le...

Matthew J. Holland, et al. ∙

research

∙ 11/30/2016

Fusion of EEG and Musical Features in Continuous Music-emotion Recognition

Emotion estimation in music listening is confronting challenges to captu...

Nattapong Thammasan, et al. ∙

research

∙ 11/27/2016

It's Written All Over Your Face: Full-Face Appearance-Based Gaze Estimation

Eye gaze is an important non-verbal cue for human affect analysis. Recen...

Xucong Zhang, et al. ∙

research

∙ 02/15/2016

Selective Inference Approach for Statistically Sound Predictive Pattern Mining

Discovering statistically significant patterns from databases is an impo...

Shinya Suzumura, et al. ∙

research

∙ 11/09/2015

Learning Instrumental Variables with Non-Gaussianity Assumptions: Theoretical Limitations and Practical Algorithms

Learning a causal effect from observational data is not straightforward,...

Ricardo Silva, et al. ∙

research

∙ 06/01/2016

Multiview Rectification of Folded Documents

Digitally unwrapping images of paper sheets is crucial for accurate docu...

Shaodi You, et al. ∙

research

∙ 03/20/2016

RotationNet: Joint Object Categorization and Pose Estimation Using Multiviews from Unsupervised Viewpoints

We propose a Convolutional Neural Network (CNN)-based model "RotationNet...

Asako Kanezaki, et al. ∙

research

∙ 07/04/2014

Identifying Higher-order Combinations of Binary Features

Finding statistically significant interactions between binary variables ...

Felipe Llinares, et al. ∙

research

∙ 07/01/2014

Significant Subgraph Mining with Multiple Testing Correction

The problem of finding itemsets that are statistically significantly enr...

Mahito Sugiyama, et al. ∙

research

∙ 01/22/2014

Causal Discovery in a Binary Exclusive-or Skew Acyclic Model: BExSAM

Discovering causal relations among observed variables in a given data se...

Takanori Inazumi, et al. ∙

research

∙ 01/22/2014

Identifiability of an Integer Modular Acyclic Additive Noise Model and its Causal Structure Discovery

The notion of causality is used in many situations dealing with uncertai...

Joe Suzuki, et al. ∙

research

∙ 01/20/2014

Anomaly detection in reconstructed quantum states using a machine-learning technique

The accurate detection of small deviations in given density matrices is ...

Satoshi Hara, et al. ∙

research

∙ 12/12/2013

Clustering for high-dimension, low-sample size data using distance vectors

In high-dimension, low-sample size (HDLSS) data, it is not always true t...

Yoshikazu Terada, et al. ∙

research

∙ 08/21/2012

Learning LiNGAM based on data with more variables than observations

A very important topic in systems biology is developing statistical meth...

Shohei Shimizu, et al. ∙

research

∙ 04/28/2011

Joint estimation of linear non-Gaussian acyclic models

A linear non-Gaussian structural equation model called LiNGAM is an iden...

Shohei Shimizu, et al. ∙

research

∙ 11/28/2017

Merlin-Arthur with efficient quantum Merlin and quantum supremacy for the second level of the Fourier hierarchy

It is a long-standing open problem whether quantum computing can be veri...

Tomoyuki Morimae, et al. ∙

research

∙ 09/27/2017

An Empirical Study on the Impact of Refactoring Activities on Evolving Client-Used APIs

Context: Refactoring is recognized as an effective practice to maintain ...

Raula Gaikovina Kula, et al. ∙

research

∙ 09/14/2017

On the Impact of Micro-Packages: An Empirical Study of the npm JavaScript Ecosystem

The rise of user-contributed Open Source Software (OSS) ecosystems demon...

Raula Gaikovina Kula, et al. ∙

research

∙ 09/14/2017

Do Developers Update Their Library Dependencies? An Empirical Study on the Impact of Security Advisories on Library Migration

Third-party library reuse has become common practice in contemporary sof...

Raula Gaikovina Kula, et al. ∙

research

∙ 01/16/2018

Plane-Casting: 3D Cursor Control with a SmartPhone

We present Plane-Casting, a novel technique for 3D object manipulation f...

Nicholas Katzakis, et al. ∙

research

∙ 01/18/2018

Forecasting User Attention During Everyday Mobile Interactions Using Device-Integrated and Wearable Sensors

Users' visual attention is highly fragmented during mobile interactions ...

Julian Steil, et al. ∙

research

∙ 01/31/2018

Data driven time scale in Gaussian quasi-likelihood inference

We study parametric estimation of ergodic diffusions observed at high fr...

Shoichi Eguchi, et al. ∙

research

∙ 03/26/2018

REST: Real-to-Synthetic Transform for Illumination Invariant Camera Localization

Accurate camera localization is an essential part of tracking systems. H...

Sota Shoman, et al. ∙

research

∙ 04/08/2018

Dimensionality's Blessing: Clustering Images by Underlying Distribution

Many high dimensional vector distances tend to a constant. This is typic...

Wen-Yan Lin, et al. ∙

research

∙ 04/17/2018

A General Formula for the Stationary Distribution of the Age of Information and Its Application to Single-Server Queues

This paper considers the stationary distribution of the age of informati...

Yoshiaki Inoue, et al. ∙

research

∙ 04/25/2018

Probabilistic Plant Modeling via Multi-View Image-to-Image Translation

This paper describes a method for inferring three-dimensional (3D) plant...

Takahiro Isokane, et al. ∙

research

∙ 05/16/2018

On the List Decodability of Insertions and Deletions

List decoding of insertions and deletions is studied. A Johnson-type upp...

Tomohiro Hayashi, et al. ∙

research

∙ 05/18/2018

Metric for Automatic Machine Translation Evaluation based on Universal Sentence Representations

Sentence representations can capture a wide range of information that ca...

Hiroki Shimanaka, et al. ∙

research

∙ 05/22/2018

Experiments on Learning Based Industrial Bin-picking with Iterative Visual Recognition

This paper shows experimental results on learning based randomized bin-p...

Kensuke Harada, et al. ∙

research

∙ 05/23/2018

Tool Exchangeable Grasp/Assembly Planner

This paper proposes a novel assembly planner for a manipulator which can...

Kensuke Harada, et al. ∙

research

∙ 05/23/2018

Learning Based Industrial Bin-picking Trained with Approximate Physics Simulator

In this research, we tackle the problem of picking an object from random...

Ryo Matsumura, et al. ∙

Osaka University

Featured Researchers