An Ensemble Framework Based on Fine Multi-Window Feature Engineering and Overfitting Prevention for Transportation Mode Recognition
Author:
Affiliation:
1. Center for Applied Statistics, School of Statistics Renmin University of China, China
2. Beijing Baixingkefu Network Technology Co., Ltd., China
Funder
National Natural Science Foundation of China
the MOE Project of Key Research Institute of Humanities and Social Sciences
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3594739.3610756
Reference12 articles.
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3. [ 3 ] Kei Yaguchi Kazukiyo Ikarigawa Ryo Kawasaki Wataru Miyazaki Yuki Morikawa Chihiro Ito Masaki Shuzo and Eisaku Maeda. 2020. Human activity recognition using multi-input CNN model with FFT spectrograms. In Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers (UbiComp-ISWC ’20). ACM 364–367. [3] Kei Yaguchi Kazukiyo Ikarigawa Ryo Kawasaki Wataru Miyazaki Yuki Morikawa Chihiro Ito Masaki Shuzo and Eisaku Maeda. 2020. Human activity recognition using multi-input CNN model with FFT spectrograms. In Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers (UbiComp-ISWC ’20). ACM 364–367.
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1. Summary of SHL Challenge 2023: Recognizing Locomotion and Transportation Mode from GPS and Motion Sensors;Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing;2023-10-08
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