An Ensemble Framework Based on Fine Multi-Window Feature Engineering and Overfitting Prevention for Transportation Mode Recognition-Reference-Cited by-同舟云学术

An Ensemble Framework Based on Fine Multi-Window Feature Engineering and Overfitting Prevention for Transportation Mode Recognition

Published:2023-10-08 Issue: Volume: Page:
ISSN:
Container-title:Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing
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Author:

Zeng Zehong¹^ORCID,Liu Yueyang¹^ORCID,Lu Xiaoshi¹^ORCID,Zhang Yuanyuan²^ORCID,Lu Xiaoling¹^ORCID

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.

1. [ 1 ] Jinhua Su and Yuanyuan Zhang. 2021. Triple-O for SHL Recognition Challenge: An Ensemble Framework for Multi-class Imbalance and Training-testing Distribution Inconsistency by OvO Binarization with Confidence Weight of One-class Classification. In Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers (UbiComp ’21). ACM 401–407. [1] Jinhua Su and Yuanyuan Zhang. 2021. Triple-O for SHL Recognition Challenge: An Ensemble Framework for Multi-class Imbalance and Training-testing Distribution Inconsistency by OvO Binarization with Confidence Weight of One-class Classification. In Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers (UbiComp ’21). ACM 401–407.

2. [ 2 ] Yan Ren. 2021. Multiple Tree Model Integration for Transportation Mode Recognition. In Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers (UbiComp ’21). ACM 385–389. [2] Yan Ren. 2021. Multiple Tree Model Integration for Transportation Mode Recognition. In Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers (UbiComp ’21). ACM 385–389.

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.

4. [ 4 ] Chan Naseeb and Bilal Al Saeedi. 2020. Activity recognition for locomotion and transportation dataset using deep learning. 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 329–334. [4] Chan Naseeb and Bilal Al Saeedi. 2020. Activity recognition for locomotion and transportation dataset using deep learning. 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 329–334.

5. [ 5 ] Björn Friedrich Carolin Lübbe and Andreas Hein. 2020. Combining LSTM and CNN for mode of transportation classification from smartphone sensors. 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 305–310 [5] Björn Friedrich Carolin Lübbe and Andreas Hein. 2020. Combining LSTM and CNN for mode of transportation classification from smartphone sensors. 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 305–310

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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