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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).
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Inferring activities from interactions with objects
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Inferring activities from interactions with objects
Matthai Philipose, Kenneth P Fishkin, Mike Perkowitz, Donald J Patterson, Dieter Fox, Henry Kautz, and Dirk Hähnel. 2004b · 2004
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Fine-grained activity recognition by aggregating abstract object usage. In Ninth IEEE International Symposium on Wearable Computers (ISWC’05) . 44–51
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A review of wearable sensors and systems with application in rehabilitation
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Toward Practical Factory Activity Recognition: Unsupervised Understanding of Repetitive Assembly Work in a Factory. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (Heidelberg, Germany) (UbiComp ’16) . Association for Computing Machinery, New York, NY, USA, 1088–1099
Takuya Maekawa, Daisuke Nakai, Kazuya Ohara, and Yasuo Namioka. 2016 · 2016
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Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition
Francisco Javier Ordóñez and Daniel Roggen. 2016 · 2016
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Recognising complex activities with histograms of relative tracklets
Sebastian Stein and Stephen J. McKenna. 2017 · 2016
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Divide and Conquer-Based 1D CNN Human Activity Recognition Using Test Data Sharpening
Generated knowledge prompting for commonsense reasoning
Jiacheng Liu, Alisa Liu, Ximing Lu, Sean Welleck, Peter West, Ronan Le Bras, Yejin Choi, and Hannaneh Hajishirzi. 2021 · 2021
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Finetuned language models are zero-shot learners
Jason Wei, Maarten Bosma, Vincent Y Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M Dai, and Quoc V Le. 2021 · 2021
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Bootstrapping Human Activity Recognition Systems for Smart Homes from Scratch
Shruthi K. Hiremath, Yasutaka Nishimura, Sonia Chernova, and Thomas Plötz. 2022 · 2022
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Acceleration-based Human Activity Recognition of Packaging Tasks Using Motif-guided Attention Networks. In Proceedings of the 2022 IEEE International Conference on Pervasive Computing and Communications (PerCom) . 1–12
Jaime Morales, Naoya Yoshimura, Qingxin Xia, Atsushi Wada, Yasuo Namioka, and Takuya Maekawa. 2022 · 2022
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Heeryon Cho and Sang Min Yoon. 2018 · 2018
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Personalizing Activity Recognition Models Through Quantifying Different Types of Uncertainty Using Wearable Sensors
Ali Akbari and Roozbeh Jafari. 2020 · 2019
Cited alongside, same era.
Integrating Activity Recognition and Nursing Care Records: The System, Deployment, and a Verification Study
Sozo Inoue, Paula Lago, Tahera Hossain, Tittaya Mairittha, and Nattaya Mairittha. 2019 · 2019
Cited alongside, same era.
Unsupervised Factory Activity Recognition with Wearable Sensors Using Process Instruction Information
Qingxin Xia, Atsushi Wada, Joseph Korpela, Takuya Maekawa, and Yasuo Namioka. 2019 · 2019
Cited alongside, same era.
Unsupervised Activity Recognition Using Automatically Mined Common Sense. In Proceedings of the 20th National Conference on Artificial Intelligence - Volume 1 (Pittsburgh, Pennsylvania) (AAAI’05) . AAAI Press, 21–27
Danny Wyatt, Matthai Philipose, and Tanzeem Choudhury. 2005b
Cited in the paper.
Naoya Yoshimura, Takuya Maekawa, Takahiro Hara, Atsushi Wada, and Yasuo Namioka. 2022 · 2022
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Pre-Train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2023 · 2023
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