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Yuuna Hoshi

3 accepted papers

2019

Adaptive Loss Balancing for Multitask Learning of Object Instance Recognition and 3D Pose Estimation

IROS 2019poster

Object instance recognition and 3D pose estimation are important elements in robot vision technology. State-of-the-art methods improve the accuracy of both instance recognition and pose estimation using multitask learning. These methods use unified balancing parameters to integrate the loss of each…

Cited by 3SourceScholar
2018

A Multimodal Anomaly Detector for Robot-Assisted Feeding Using an LSTM-Based Variational Autoencoder

RA-L 2018

The detection of anomalous executions is valuable for reducing potential hazards in assistive manipulation. Multimodal sensory signals can be helpful for detecting a wide range of anomalies. However, the fusion of high-dimensional and heterogeneous modalities is a challenging problem for model-based

Cited by 1001SourceScholar
2017

A multimodal execution monitor with anomaly classification for robot-assisted feeding

IROS 2017poster

Activities of daily living (ADLs) are important for quality of life. Robotic assistance offers the opportunity for people with disabilities to perform ADLs on their own. However, when a complex semi-autonomous system provides real-world assistance, occasional anomalies are likely to occur. Robots th…

Cited by 84SourceScholar