Name
Title | ||
|---|---|---|
Hierarchical classification using ML/DL for sussex-huawei locomotion-transportation (SHL) recognition challenge |
Abstract | ||
|---|---|---|
In this paper, our team, SensingGO, presents a hierarchical classifier for Sussex-Huawei Locomotion-Transportation (SHL) recognition challenge. We first separate the original data into motorized activities and non-motorized activities in the first layer of the classifier by using accelerometer data. For the non-motorized activities, we calculate auto-correlation values with accelerometer data as input features. For the motorized activities, we take magnetometer and barometer with mean, maximum, standard deviation values as input features. Finally, we integrate the recognition results of each layer of the classifier, and the average F1-score is 50% to the validation data.
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Year | DOI | Venue |
|---|---|---|
2020 | 10.1145/3410530.3414347 | UbiComp/ISWC '20: 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2020 ACM International Symposium on Wearable Computers
Virtual Event
Mexico
September, 2020 |
DocType | ISBN | Citations |
Conference | 978-1-4503-8076-8 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yi-Ting Tseng | 1 | 5 | 1.38 |
| Hsien-Ting Lin | 2 | 0 | 0.34 |
| Yi-Hao Lin | 3 | 1 | 2.84 |
| Jyh-Cheng Chen | 4 | 1204 | 146.68 |