{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T15:33:05Z","timestamp":1775143985770,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":30,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,9,10]],"date-time":"2020-09-10T00:00:00Z","timestamp":1599696000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,9,10]]},"DOI":"10.1145\/3410530.3414367","type":"proceedings-article","created":{"date-parts":[[2020,9,12]],"date-time":"2020-09-12T19:56:53Z","timestamp":1599940613000},"page":"249-254","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":63,"title":["ActivityGAN"],"prefix":"10.1145","author":[{"given":"Xi'ang","family":"Li","sequence":"first","affiliation":[{"name":"Huazhong University of Science and, Technology, China"}]},{"given":"Jinqi","family":"Luo","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore"}]},{"given":"Rabih","family":"Younes","sequence":"additional","affiliation":[{"name":"Duke University"}]}],"member":"320","published-online":{"date-parts":[[2020,9,12]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/PERCOMW.2017.7917555"},{"key":"e_1_3_2_1_2_1","volume-title":"Wasserstein gan. arXiv preprint arXiv:1701.07875","author":"Arjovsky Martin","year":"2017","unstructured":"Martin Arjovsky , Soumith Chintala , and L\u00e9on Bottou . 2017. Wasserstein gan. arXiv preprint arXiv:1701.07875 ( 2017 ). Martin Arjovsky, Soumith Chintala, and L\u00e9on Bottou. 2017. Wasserstein gan. arXiv preprint arXiv:1701.07875 (2017)."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3341162.3344854"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.3390\/s140406474"},{"key":"e_1_3_2_1_5_1","unstructured":"Akram Bayat Marc Pomplun and Duc A Tran. [n.d.]. A study on human activity recognition using accelerometer data from smartphones. Procedia Computer Science ([n. d.]).  Akram Bayat Marc Pomplun and Duc A Tran. [n.d.]. A study on human activity recognition using accelerometer data from smartphones. Procedia Computer Science ([n. d.])."},{"key":"e_1_3_2_1_6_1","volume-title":"BEGAN: Boundary Equilibrium Generative Adversarial Networks.","author":"Berthelot David","year":"2017","unstructured":"David Berthelot , Tom Schumm , and Luke Metz . 2017 . BEGAN: Boundary Equilibrium Generative Adversarial Networks. (2017). David Berthelot, Tom Schumm, and Luke Metz. 2017. BEGAN: Boundary Equilibrium Generative Adversarial Networks. (2017)."},{"key":"e_1_3_2_1_7_1","volume-title":"Kempa-Liehr","author":"Christ Maximilian","year":"2018","unstructured":"Maximilian Christ , Nils Braun , Julius Neuffer , and Andreas W . Kempa-Liehr . 2018 . Time Series FeatuRe Extraction on basis of Scalable Hypothesis tests (tsfresh - A Python package). Neurocomputing (2018), S0925231218304843. Maximilian Christ, Nils Braun, Julius Neuffer, and Andreas W. Kempa-Liehr. 2018. Time Series FeatuRe Extraction on basis of Scalable Hypothesis tests (tsfresh - A Python package). Neurocomputing (2018), S0925231218304843."},{"key":"e_1_3_2_1_8_1","volume-title":"NIPS 2016 Tutorial: Generative Adversarial Networks. arXiv:1701","author":"Goodfellow Ian","year":"2016","unstructured":"Ian Goodfellow . 2016 . NIPS 2016 Tutorial: Generative Adversarial Networks. arXiv:1701 .00160 [cs.LG] Ian Goodfellow. 2016. NIPS 2016 Tutorial: Generative Adversarial Networks. arXiv:1701.00160 [cs.LG]"},{"key":"e_1_3_2_1_9_1","unstructured":"Ian Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville and Yoshua Bengio. 2014. Generative adversarial nets. In Advances in neural information processing systems. 2672--2680.  Ian Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville and Yoshua Bengio. 2014. Generative adversarial nets. In Advances in neural information processing systems. 2672--2680."},{"key":"e_1_3_2_1_10_1","unstructured":"Ishaan Gulrajani Faruk Ahmed Martin Arjovsky Vincent Dumoulin and Aaron C Courville. 2017. Improved training of wasserstein gans. In Advances in neural information processing systems. 5767--5777.  Ishaan Gulrajani Faruk Ahmed Martin Arjovsky Vincent Dumoulin and Aaron C Courville. 2017. Improved training of wasserstein gans. In Advances in neural information processing systems. 5767--5777."},{"key":"e_1_3_2_1_11_1","volume-title":"Real-time human activity recognition from accelerometer data using Convolutional Neural Networks. Applied Soft Computing","author":"Ignatov Andrey","year":"2018","unstructured":"Andrey Ignatov . 2018. Real-time human activity recognition from accelerometer data using Convolutional Neural Networks. Applied Soft Computing ( 2018 ). Andrey Ignatov. 2018. Real-time human activity recognition from accelerometer data using Convolutional Neural Networks. Applied Soft Computing (2018)."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/2733373.2806333"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2030112.2030218"},{"key":"e_1_3_2_1_14_1","volume-title":"A survey on human activity recognition using wearable sensors","author":"Lara Oscar D","year":"2012","unstructured":"Oscar D Lara and Miguel A Labrador . 2012. A survey on human activity recognition using wearable sensors . IEEE communications surveys & tutorials ( 2012 ). Oscar D Lara and Miguel A Labrador. 2012. A survey on human activity recognition using wearable sensors. IEEE communications surveys & tutorials (2012)."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2018.8363749"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.304"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2018.03.056"},{"key":"e_1_3_2_1_18_1","volume-title":"Semi-supervised learning with generative adversarial networks. arXiv:1606.01583","author":"Odena Augustus","year":"2016","unstructured":"Augustus Odena . 2016. Semi-supervised learning with generative adversarial networks. arXiv:1606.01583 ( 2016 ). Augustus Odena. 2016. Semi-supervised learning with generative adversarial networks. arXiv:1606.01583 (2016)."},{"key":"e_1_3_2_1_19_1","volume-title":"International conference on machine learning. 1310--1318","author":"Pascanu Razvan","year":"2013","unstructured":"Razvan Pascanu , Tomas Mikolov , and Yoshua Bengio . 2013 . On the difficulty of training recurrent neural networks . In International conference on machine learning. 1310--1318 . Razvan Pascanu, Tomas Mikolov, and Yoshua Bengio. 2013. On the difficulty of training recurrent neural networks. In International conference on machine learning. 1310--1318."},{"key":"e_1_3_2_1_20_1","volume-title":"SEGAN: Speech enhancement generative adversarial network. arXiv:1703.09452","author":"Pascual Santiago","year":"2017","unstructured":"Santiago Pascual , Antonio Bonafonte , and Joan Serra . 2017 . SEGAN: Speech enhancement generative adversarial network. arXiv:1703.09452 (2017). Santiago Pascual, Antonio Bonafonte, and Joan Serra. 2017. SEGAN: Speech enhancement generative adversarial network. arXiv:1703.09452 (2017)."},{"key":"e_1_3_2_1_21_1","volume-title":"Language generation with recurrent generative adversarial networks without pre-training. arXiv:1706.01399","author":"Press Ofir","year":"2017","unstructured":"Ofir Press , Amir Bar , Ben Bogin , Jonathan Berant , and Lior Wolf . 2017. Language generation with recurrent generative adversarial networks without pre-training. arXiv:1706.01399 ( 2017 ). Ofir Press, Amir Bar, Ben Bogin, Jonathan Berant, and Lior Wolf. 2017. Language generation with recurrent generative adversarial networks without pre-training. arXiv:1706.01399 (2017)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2017.10.011"},{"key":"e_1_3_2_1_23_1","volume-title":"Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434","author":"Radford Alec","year":"2015","unstructured":"Alec Radford , Luke Metz , and Soumith Chintala . 2015. Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434 ( 2015 ). Alec Radford, Luke Metz, and Soumith Chintala. 2015. Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434 (2015)."},{"key":"e_1_3_2_1_24_1","unstructured":"Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford and Xi Chen. 2016. Improved techniques for training gans. In Advances in neural information processing systems. 2234--2242.  Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford and Xi Chen. 2016. Improved techniques for training gans. In Advances in neural information processing systems. 2234--2242."},{"key":"e_1_3_2_1_25_1","volume-title":"Unsupervised and semi-supervised learning with categorical generative adversarial networks. arXiv","author":"Springenberg Jost Tobias","year":"2015","unstructured":"Jost Tobias Springenberg . 2015. Unsupervised and semi-supervised learning with categorical generative adversarial networks. arXiv ( 2015 ). Jost Tobias Springenberg. 2015. Unsupervised and semi-supervised learning with categorical generative adversarial networks. arXiv (2015)."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.141"},{"key":"e_1_3_2_1_27_1","volume-title":"Semi-supervised learning with generative adversarial networks on digital signal modulation classification. Comput. Mater. Continua","author":"Tu Ya","year":"2018","unstructured":"Ya Tu , Yun Lin , Jin Wang , and Jeong-Uk Kim . 2018. Semi-supervised learning with generative adversarial networks on digital signal modulation classification. Comput. Mater. Continua ( 2018 ). Ya Tu, Yun Lin, Jin Wang, and Jeong-Uk Kim. 2018. Semi-supervised learning with generative adversarial networks on digital signal modulation classification. Comput. Mater. Continua (2018)."},{"key":"e_1_3_2_1_28_1","volume-title":"SensoryGANs: An Effective Generative Adversarial Framework for Sensor-based Human Activity Recognition. In 2018 International Joint Conference on Neural Networks (IJCNN). IEEE, 1--8.","author":"Wang Jiwei","year":"2018","unstructured":"Jiwei Wang , Yiqiang Chen , Yang Gu , Yunlong Xiao , and Haonan Pan . 2018 . SensoryGANs: An Effective Generative Adversarial Framework for Sensor-based Human Activity Recognition. In 2018 International Joint Conference on Neural Networks (IJCNN). IEEE, 1--8. Jiwei Wang, Yiqiang Chen, Yang Gu, Yunlong Xiao, and Haonan Pan. 2018. SensoryGANs: An Effective Generative Adversarial Framework for Sensor-based Human Activity Recognition. In 2018 International Joint Conference on Neural Networks (IJCNN). IEEE, 1--8."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3264954"},{"key":"e_1_3_2_1_30_1","volume-title":"Electrocardiogram generation with a bidirectional LSTM-CNN generative adversarial network. Scientific reports","author":"Zhu Fei","year":"2019","unstructured":"Fei Zhu , Fei Ye , Yuchen Fu , Quan Liu , and Bairong Shen . 2019. Electrocardiogram generation with a bidirectional LSTM-CNN generative adversarial network. Scientific reports ( 2019 ). Fei Zhu, Fei Ye, Yuchen Fu, Quan Liu, and Bairong Shen. 2019. Electrocardiogram generation with a bidirectional LSTM-CNN generative adversarial network. Scientific reports (2019)."}],"event":{"name":"UbiComp\/ISWC '20: 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2020 ACM International Symposium on Wearable Computers","location":"Virtual Event Mexico","acronym":"UbiComp\/ISWC '20","sponsor":["SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing","SIGCHI ACM Special Interest Group on Computer-Human Interaction"]},"container-title":["Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3410530.3414367","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3410530.3414367","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:31:59Z","timestamp":1750195919000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3410530.3414367"}},"subtitle":["generative adversarial networks for data augmentation in sensor-based human activity recognition"],"short-title":[],"issued":{"date-parts":[[2020,9,10]]},"references-count":30,"alternative-id":["10.1145\/3410530.3414367","10.1145\/3410530"],"URL":"https:\/\/doi.org\/10.1145\/3410530.3414367","relation":{},"subject":[],"published":{"date-parts":[[2020,9,10]]},"assertion":[{"value":"2020-09-12","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}