Three-year review of the 2018–2020 SHL challenge on transportation and locomotion mode recognition from mobile sensors
The Sussex-Huawei Locomotion-Transportation (SHL) Recognition Challenges aim to
advance and capture the state-of-the-art in locomotion and transportation mode recognition …
advance and capture the state-of-the-art in locomotion and transportation mode recognition …
Summary of SHL challenge 2023: Recognizing locomotion and transportation mode from GPS and motion sensors
In this paper we summarize the contributions of participants to the fifth Sussex-Huawei
Locomotion-Transportation (SHL) Recognition Challenge organized at the HASCA …
Locomotion-Transportation (SHL) Recognition Challenge organized at the HASCA …
MobilityDL: a review of deep learning from trajectory data
Trajectory data combines the complexities of time series, spatial data, and (sometimes
irrational) movement behavior. As data availability and computing power have increased, so …
irrational) movement behavior. As data availability and computing power have increased, so …
Biosensor-driven IoT wearables for accurate body motion tracking and localization
The domain of human locomotion identification through smartphone sensors is witnessing
rapid expansion within the realm of research. This domain boasts significant potential across …
rapid expansion within the realm of research. This domain boasts significant potential across …
A multimodal IoT-based locomotion classification system using features engineering and Recursive neural network
Locomotion prediction for human welfare has gained tremendous interest in the past few
years. Multimodal locomotion prediction is composed of small activities of daily living and an …
years. Multimodal locomotion prediction is composed of small activities of daily living and an …
ModeSense: Ubiquitous and accurate transportation mode detection using serving cell tower information
Recent transportation mode detection systems propose leveraging signals from only the
serving cell tower to ensure ubiquity and practical deployability across all phones. However …
serving cell tower to ensure ubiquity and practical deployability across all phones. However …
Human activity recognition with AutoML using smartphone radio data
D Balabka, D Shkliarenko - Adjunct Proceedings of the 2021 ACM …, 2021 - dl.acm.org
Participants of the fourth edition of SHL recognition challenge 2021 aim to recognize eight
locomotion and transportation activities in a user-independent manner based on radio data …
locomotion and transportation activities in a user-independent manner based on radio data …
[PDF][PDF] Deep Learning From Trajectory Data: a Review of Deep Neural Networks and the Trajectory Data Representations to Train Them.
Trajectory data combines the complexities of time series, spatial data, and (sometimes
irrational) movement behavior. As data availability and computing power have increased, so …
irrational) movement behavior. As data availability and computing power have increased, so …
Phased human activity recognition based on GPS
R Sekiguchi, K Abe, suzuki shogo, M Kumano… - Adjunct Proceedings of …, 2021 - dl.acm.org
This paper describes an activity recognition method for Sussex-Huawei Locomotion-
Transportation (SHL) recognition challenge by team TDU_BSA_BCI. The classification …
Transportation (SHL) recognition challenge by team TDU_BSA_BCI. The classification …
Multiple tree model integration for transportation mode recognition
Y Ren - Adjunct Proceedings of the 2021 ACM International …, 2021 - dl.acm.org
The team RY presents a solution for Sussex-Huawei Locomotion-Transportation (SHL)
recognition challenge, which aims at differentiating eight transportation modes with mobile …
recognition challenge, which aims at differentiating eight transportation modes with mobile …