SHL行動認識チャレンジ@HASCA/UbiComp2018シンガポール

[Kazuya Murao]

HASCの皆様
立命館大学　村尾です．お世話になっております．

今年もHASCA2018をUbiComp2018@シンガポールの併設ワークショップとして開催します．
論文募集に先立ちまして，HASCA2018ではSHL Activity Recognition Challengeという
人間行動認識の精度を競う大会を開催しますので，案内させていただきます．

開催形式は，公開された学習データ＋テストデータをもとに，
テストデータの認識結果の提出＋アルゴリズムの説明をしたHASCAの原稿提出

をしていただき，成績上位者はHASCA2018で発表していただく形です．

上位3チームには賞金もあります！

行動認識にご興味のある皆様，ぜひご参加ください．

参加登録は6/20までです．

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We are glad to inform you about the SHL Activity Recognition Challenge (http://www.shl-dataset.org/activity-recognition-challenge/).

The goal of this machine learning/data science challenge is to recognize 8 modes of locomotion and transportation (activities) from the inertial sensor data of a smartphone. The dataset used for this challenge comprises 271 hours of training data and 95 hours of test data.

The participants will have to develop an algorithm pipeline that will process the sensor data, create models and output the recognized activities. The best three teams will also receive prizes!

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 2018. 

The timeline of the challenge:

- Registration via email: as soon as possible, but not later than 20.06.2018

- Challenge duration: 01.06.2018 - 15.07.2018

- Submission deadline: 15.07.2018

- HASCA paper submission: TBA (tentative: 31.07.2018)

- HASCA Workshop presentation: TBA (tentative: 08 or 12.10.2018)

Organizers:

- Dr. Hristijan Gjoreski, University of Sussex (UK) & Ss. Cyril and Methodius University (MK)

- Dr. Lin Wang, University of Sussex (UK)

- Dr. Daniel Roggen, University of Sussex (UK)

- Dr. Kazuya Murao, Ritsumeikan University (JP)

Contact:

All inquiries should be directed to: shldataset...@gmail.com

--

村尾和哉(立命館大学情報理工学部 准教授) / Kazuya MURAO, Associate Professor, Dr.

College of Info. Sci. and Eng., Ritsumeikan Univ. 1-1-1 Nojihigashi, Kusatsu, Shiga 525-8577, Japan

mu...@cs.ritsumei.ac.jp     http://www.muraokazuya.net