SHL Activity Recognition Challenge @HASCA/Ubicomp 2023 (fifth edition)
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linwa...@gmail.com
Apr 12, 2023, 4:05:26 PM4/12/23
to Machine Learning News
Dear colleagues,
The Wearable Technologies Lab at the University of Sussex is glad to inform you about the fifth SHL Activity Recognition Challenge (http://www.shl-dataset.org/activity-recognition-challenge-2023/).
This follows on our very successful 2018, 2019, 2020 and 2021 challenges, which saw the participation of more than 100 teams and 250 researchers in total.
This 2023 edition focuses on recognising 8 modes of locomotion and transportation (activities) in a user-independent manner based on motion (accelerometer, gyroscope, magnetometer) and GPS (satellite and location) data.
The training data is made of the existing published SHL data (about 6 months). The training data will be a few days from an unknown new user.
The participants will have to develop an algorithm pipeline that will process the sensor data, create models and output the recognized activities.
All teams will receive a certificate of participation, and the best three teams will also receive a prize (800£, 400£ and 200£).
The participants should also write a technical paper explaining their methods and development process, which will be presented at a special session at the HASCA Workshop at Ubicomp 2023, and included in the adjunct proceedings.
The timeline of the challenge:
Registration via email: as soon as possible, but not later than 30.04.2023
Challenge duration: 20.04.2023 – 30.06.2023
Submission deadline: 30.06.2023
HASCA-SHL paper submission: 10.07.2023
HASCA Workshop presentation: TBD
Organizers:
- Dr. Lin Wang, Queen Mary University of London (UK)
- Dr. Daniel Roggen
- Dr. Hristijan Gjoreski, Ss. Cyril and Methodius University (MK)
- Dr. Mathias Ciliberto, University of Sussex (UK)
- Dr. Kazuya Murao, Ritsumeikan University (JP)
- Dr. Tsuyoshi Okita, Kyushu Institute of Technology (JP)
- Dr. Paula Lago, Concordia University in Montreal (CA)
Contact:
All inquiries should be directed to: shldataset...@gmail.com
Best regards,
SHL Team
The Wearable Technologies Lab at the University of Sussex is glad to inform you about the fifth SHL Activity Recognition Challenge (http://www.shl-dataset.org/activity-recognition-challenge-2023/).
This follows on our very successful 2018, 2019, 2020 and 2021 challenges, which saw the participation of more than 100 teams and 250 researchers in total.
This 2023 edition focuses on recognising 8 modes of locomotion and transportation (activities) in a user-independent manner based on motion (accelerometer, gyroscope, magnetometer) and GPS (satellite and location) data.
The training data is made of the existing published SHL data (about 6 months). The training data will be a few days from an unknown new user.
The participants will have to develop an algorithm pipeline that will process the sensor data, create models and output the recognized activities.
All teams will receive a certificate of participation, and the best three teams will also receive a prize (800£, 400£ and 200£).
The participants should also write a technical paper explaining their methods and development process, which will be presented at a special session at the HASCA Workshop at Ubicomp 2023, and included in the adjunct proceedings.
The timeline of the challenge:
Registration via email: as soon as possible, but not later than 30.04.2023
Challenge duration: 20.04.2023 – 30.06.2023
Submission deadline: 30.06.2023
HASCA-SHL paper submission: 10.07.2023
HASCA Workshop presentation: TBD
Organizers:
- Dr. Lin Wang, Queen Mary University of London (UK)
- Dr. Daniel Roggen
- Dr. Hristijan Gjoreski, Ss. Cyril and Methodius University (MK)
- Dr. Mathias Ciliberto, University of Sussex (UK)
- Dr. Kazuya Murao, Ritsumeikan University (JP)
- Dr. Tsuyoshi Okita, Kyushu Institute of Technology (JP)
- Dr. Paula Lago, Concordia University in Montreal (CA)
Contact:
All inquiries should be directed to: shldataset...@gmail.com
Best regards,
SHL Team
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