Tackling the SHL challenge 2020 with person-specific classifiers and semi-supervised learning

Author:

Kalabakov Stefan1,Stankoski Simon1,Reščič Nina1,Kiprijanovska Ivana1,Andova Andrejaana1,Picard Clement2,Janko Vito3,Gjoreski Martin1,Luštrek Mitja1

Affiliation:

1. Jožef Stefan Institute, Ljubljana, Slovenia

2. ENS Rennes, Rennes, France

3. Jožef Stefan Institute Ljubljana, Slovenia

Publisher

ACM

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Enhancing Locomotion Recognition with Specialized Features and Map Information via XGBoost;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

2. Enhancing XGBoost with Heuristic Smoothing for Transportation Mode and Activity Recognition;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

3. AttenDenseNet for the Sussex-Huawei Locomotion-Transportation (SHL) Recognition Challenge;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

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

5. Enhanced SHL Recognition Using Machine Learning and Deep Learning Models with Multi-source Data;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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