Zobrazeno 1 - 10
of 158
pro vyhledávání: '"Maekawa, Takuya"'
Preliminary Investigation of SSL for Complex Work Activity Recognition in Industrial Domain via MoIL
Autor:
Xia, Qingxin, Maekawa, Takuya, Morales, Jaime, Hara, Takahiro, Oshima, Hirotomo, Fukuda, Masamitsu, Namioka, Yasuo
In this study, we investigate a new self-supervised learning (SSL) approach for complex work activity recognition using wearable sensors. Owing to the cost of labeled sensor data collection, SSL methods for human activity recognition (HAR) that effec
Externí odkaz:
http://arxiv.org/abs/2404.13581
Wearable sensor devices, which offer the advantage of recording daily objects used by a person while performing an activity, enable the feasibility of unsupervised Human Activity Recognition (HAR). Unfortunately, previous unsupervised approaches usin
Externí odkaz:
http://arxiv.org/abs/2306.02140
Autor:
Hoffman, Benjamin, Cusimano, Maddie, Baglione, Vittorio, Canestrari, Daniela, Chevallier, Damien, DeSantis, Dominic L., Jeantet, Lorène, Ladds, Monique A., Maekawa, Takuya, Mata-Silva, Vicente, Moreno-González, Víctor, Pagano, Anthony, Trapote, Eva, Vainio, Outi, Vehkaoja, Antti, Yoda, Ken, Zacarian, Katherine, Friedlaender, Ari
Animal-borne sensors (`bio-loggers') can record a suite of kinematic and environmental data, which are used to elucidate animal ecophysiology and improve conservation efforts. Machine learning techniques are used for interpreting the large amounts of
Externí odkaz:
http://arxiv.org/abs/2305.10740
OpenPack: A Large-scale Dataset for Recognizing Packaging Works in IoT-enabled Logistic Environments
Publikováno v:
Proceedings of IEEE International Conference on Pervasive Computing and Communications (PerCom), March 2024, pp. 90-97
Unlike human daily activities, existing publicly available sensor datasets for work activity recognition in industrial domains are limited by difficulties in collecting realistic data as close collaboration with industrial sites is required. This als
Externí odkaz:
http://arxiv.org/abs/2212.11152
In recommender systems, a cold-start problem occurs when there is no past interaction record associated with the user or item. Typical solutions to the cold-start problem make use of contextual information, such as user demographic attributes or prod
Externí odkaz:
http://arxiv.org/abs/2106.02256
Autor:
Kumrai, Teerawat, Korpela, Joseph, Zhang, Yizhe, Ohara, Kazuya, Murakami, Tomoki, Abeysekera, Hirantha, Maekawa, Takuya
Publikováno v:
In Pervasive and Mobile Computing February 2023 89
Autor:
Morales, Jaime, Yoshimura, Naoya, Xia, Qingxin, Wada, Atsushi, Namioka, Yasuo, Maekawa, Takuya
Publikováno v:
In Pervasive and Mobile Computing January 2023 88
Akademický článek
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Autor:
Li, Zhi, Amagata, Daichi, Zhang, Yihong, Maekawa, Takuya, Hara, Takahiro, Yonekawa, Kei, Kurokawa, Mori
Publikováno v:
In Knowledge-Based Systems 14 November 2022 255
Autor:
Nakasaki, Kiyohiko, Nguyen, Kiem Khac, Ballesteros, Florencio C., Jr., Maekawa, Takuya, Koyama, Mitsuhiko
Publikováno v:
In Anaerobe February 2020 61