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Advanced Topics in Mobile Communications (AToMIC) 2018: Difference between revisions
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Advanced Topics in Mobile Communications (AToMIC) 2018 (view source)
Revision as of 13:26, 21 November 2018
, 21 November 2018→Final Presentations & Report
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* 24 January 2019 | * 24 January 2019 | ||
**'''Deep Learning Based Human Activity Recognition''' | **'''Deep Learning Based Human Activity Recognition''' | ||
***Liangying Peng, Ling Chen, Zhenan Ye and Yi Zhang, [https://dl.acm.org/citation.cfm?id=3214277 AROMA: A Deep Multi-Task Learning Based Simple and Complex Human Activity Recognition Method Using Wearable Sensors], | ***Liangying Peng, Ling Chen, Zhenan Ye and Yi Zhang, [https://dl.acm.org/citation.cfm?id=3214277 AROMA: A Deep Multi-Task Learning Based Simple and Complex Human Activity Recognition Method Using Wearable Sensors], ACM UbiComp 2018. ('''Presented by Yachao Shao''') | ||
***Shuochao Yao, Yiran Zhao, Huajie Shao, Chao Zhang, Aston Zhang, Shaohan Hu, Dongxin Liu, Shengzhong Liu, Lu su and Tarek Abdelzaher, [https://dl.acm.org/citation.cfm?id=3264954 SenseGAN: Enabling Deep Learning for Internet of Things with a Semi-Supervised Framework], | ***Shuochao Yao, Yiran Zhao, Huajie Shao, Chao Zhang, Aston Zhang, Shaohan Hu, Dongxin Liu, Shengzhong Liu, Lu su and Tarek Abdelzaher, [https://dl.acm.org/citation.cfm?id=3264954 SenseGAN: Enabling Deep Learning for Internet of Things with a Semi-Supervised Framework], ACM UbiComp 2018. ('''Presented by Tasnia Ashrafi Heya''') | ||
***Abhinav Mehrotra and Mirco Musolesi, [https://dl.acm.org/citation.cfm?id=3264937 Using Autoencoders to Automatically Extract Mobility Features for Predicting Depressive States], | ***Abhinav Mehrotra and Mirco Musolesi, [https://dl.acm.org/citation.cfm?id=3264937 Using Autoencoders to Automatically Extract Mobility Features for Predicting Depressive States], ACM UbiComp 2018. ('''Presented by Shichang Ding''') | ||