Effectiveness of Feature Extraction System for Multimodal Sensor Information Based on VRAE and Its Application to Object Recognition
Summary :
To achieve object recognition, it is necessary to find the unique features of the objects to be recognized. Results in prior research suggest that methods that use multiple modalities information are effective to find the unique features. In this paper, the overview of the system that can extract the features of the objects to be recognized by integrating visual, tactile, and auditory information as multimodal sensor information with VRAE is shown. Furthermore, a discussion about changing the combination of modalities information is also shown.
- Publication
- IEICE TRANSACTIONS on Information Vol.E106-D No.5 pp.833-835
- Publication Date
- 2023/05/01
- Publicized
- 2023/01/12
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2022DLL0008
- Type of Manuscript
- Special Section LETTER (Special Section on Deep Learning Technologies: Architecture, Optimization, Techniques, and Applications)
- Category
- Object Recognition and Tracking
Authors
Kazuki HAYASHI
National Institute of Technology (KOSEN), Niihama College
Daisuke TANAKA
National Institute of Technology (KOSEN), Niihama College
Keyword
Latest Issue
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Kazuki HAYASHI, Daisuke TANAKA, "Effectiveness of Feature Extraction System for Multimodal Sensor Information Based on VRAE and Its Application to Object Recognition" in IEICE TRANSACTIONS on Information,
vol. E106-D, no. 5, pp. 833-835, May 2023, doi: 10.1587/transinf.2022DLL0008.
Abstract: To achieve object recognition, it is necessary to find the unique features of the objects to be recognized. Results in prior research suggest that methods that use multiple modalities information are effective to find the unique features. In this paper, the overview of the system that can extract the features of the objects to be recognized by integrating visual, tactile, and auditory information as multimodal sensor information with VRAE is shown. Furthermore, a discussion about changing the combination of modalities information is also shown.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2022DLL0008/_p
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@ARTICLE{e106-d_5_833,
author={Kazuki HAYASHI, Daisuke TANAKA, },
journal={IEICE TRANSACTIONS on Information},
title={Effectiveness of Feature Extraction System for Multimodal Sensor Information Based on VRAE and Its Application to Object Recognition},
year={2023},
volume={E106-D},
number={5},
pages={833-835},
abstract={To achieve object recognition, it is necessary to find the unique features of the objects to be recognized. Results in prior research suggest that methods that use multiple modalities information are effective to find the unique features. In this paper, the overview of the system that can extract the features of the objects to be recognized by integrating visual, tactile, and auditory information as multimodal sensor information with VRAE is shown. Furthermore, a discussion about changing the combination of modalities information is also shown.},
keywords={},
doi={10.1587/transinf.2022DLL0008},
ISSN={1745-1361},
month={May},}
Copy
TY - JOUR
TI - Effectiveness of Feature Extraction System for Multimodal Sensor Information Based on VRAE and Its Application to Object Recognition
T2 - IEICE TRANSACTIONS on Information
SP - 833
EP - 835
AU - Kazuki HAYASHI
AU - Daisuke TANAKA
PY - 2023
DO - 10.1587/transinf.2022DLL0008
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E106-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2023
AB - To achieve object recognition, it is necessary to find the unique features of the objects to be recognized. Results in prior research suggest that methods that use multiple modalities information are effective to find the unique features. In this paper, the overview of the system that can extract the features of the objects to be recognized by integrating visual, tactile, and auditory information as multimodal sensor information with VRAE is shown. Furthermore, a discussion about changing the combination of modalities information is also shown.
ER -
English
