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The usage of smartphone-collected respiratory sound, trained with deep learning models, for detecting and classifying COVID-19 becomes popular recently.
Long Short-term Memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
An efficient MFCC extraction method in speech recognition. In 2006 IEEE international symposium on circuits and systems . IEEE, 4–pp
Wei Han, Cheong-Fat Chan, Chiu-Sing Choy, and Kong-Pang Pun. 2006 · 2006
Earlier work this paper cites.
Feature extraction for the differentiation of dry and wet cough sounds. In 2011 IEEE international symposium on medical measurements and applications . IEEE, 162–166
Hanieh Chatrzarrin, Amaya Arcelus, Rafik Goubran, and Frank Knoefel. 2011 · 2011
Earlier work this paper cites.
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman. 2014 · 2014
Earlier work this paper cites.
DeepCough: A deep convolutional neural network in a wearable cough detection system. In 2015 IEEE Biomedical Circuits and Systems Conference (BioCAS) . IEEE, 1–4
Justice Amoh and Kofi Odame. 2015 · 2015
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings , Yoshua Bengio and Yann LeCun (Eds.)
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
Earlier work this paper cites.
Deep neural networks for identifying cough sounds
Justice Amoh and Kofi Odame. 2016 · 2016
Earlier work this paper cites.
Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition . 770–778
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
Earlier work this paper cites.
Energy-efficient respiratory sounds sensing for personal mobile asthma monitoring
Dinko Oletic and Vedran Bilas. 2016 · 2016
Earlier work this paper cites.
Audio set: An ontology and human-labeled dataset for audio events. In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 776–780
Jort F Gemmeke, Daniel PW Ellis, Dylan Freedman, Aren Jansen, Wade Lawrence, R Channing Moore, Manoj Plakal, and Marvin Ritter. 2017 · 2017
Earlier work this paper cites.
CNN architectures for large-scale audio classification. In 2017 ieee international conference on acoustics, speech and signal processing (icassp) . IEEE, 131–135
Shawn Hershey, Sourish Chaudhuri, Daniel PW Ellis, Jort F Gemmeke, Aren Jansen, R Channing Moore, Manoj Plakal, Devin Platt, Rif A Saurous, Bryan Seybold, et al · 2017
Cited alongside, same era.
Design of wearable breathing sound monitoring system for real-time wheeze detection
Shih-Hong Li, Bor-Shing Lin, Chen-Han Tsai, Cheng-Ta Yang, and Bor-Shyh Lin. 2017 · 2017
Cited alongside, same era.
Attention is all you need. In Proceedings of the 31st International Conference on Neural Information Processing Systems . 6000–6010
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals. 2018 · 2018
Cited alongside, same era.
Momentum contrast for unsupervised visual representation learning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 9729–9738
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick. 2020 · 2020
Later among the works it cites.
AI4COVID-19: AI enabled preliminary diagnosis for COVID-19 from cough samples via an app
Ali Imran, Iryna Posokhova, Haneya N Qureshi, Usama Masood, Muhammad Sajid Riaz, Kamran Ali, Charles N John, MD Iftikhar Hussain, and Muhammad Nabeel. 2020 · 2020
Later among the works it cites.
Dongwei Jiang, Wubo Li, Miao Cao, Ruixiong Zhang, Wei Zou, Kun Han, and Xiangang Li. 2020 · 2020
Later among the works it cites.
The COUGHVID crowdsourcing dataset: A corpus for the study of large-scale cough analysis algorithms
Lara Orlandic, Tomas Teijeiro, and David Atienza. 2020 · 2020
Later among the works it cites.
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, , Jill Burstein, Christy Doran, and Thamar Solorio (Eds.). 4171–4186
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Efficientnet: Rethinking model scaling for convolutional neural networks. In International Conference on Machine Learning . PMLR, 6105–6114
Mingxing Tan and Quoc Le. 2019 · 2019
Cited alongside, same era.
Cough against covid: Evidence of covid-19 signature in cough sounds
Piyush Bagad, Aman Dalmia, Jigar Doshi, Arsha Nagrani, Parag Bhamare, Amrita Mahale, Saurabh Rane, Neeraj Agarwal, and Rahul Panicker. 2020 · 2020
Cited alongside, same era.
Can machine learning be used to recognize and diagnose coughs?. In 2020 International Conference on e-Health and Bioengineering (EHB) . IEEE, 1–4
Charles Bales, Muhammad Nabeel, Charles N John, Usama Masood, Haneya N Qureshi, Hasan Farooq, Iryna Posokhova, and Ali Imran. 2020 · 2020
Cited alongside, same era.
Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data. In KDD ’20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual Event, CA, USA, August 23-27, 2020 , Rajesh Gupta, Yan Liu, Jiliang Tang, and B. Aditya Prakash (Eds.). ACM, 3474–3484
Chloë Brown, Jagmohan Chauhan, Andreas Grammenos, Jing Han, Apinan Hasthanasombat, Dimitris Spathis, Tong Xia, Pietro Cicuta, and Cecilia Mascolo. 2020 · 2020
Cited alongside, same era.
A simple framework for contrastive learning of visual representations. In International conference on machine learning . PMLR, 1597–1607
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton. 2020 · 2020
Cited alongside, same era.
Covid-19 detection system using recurrent neural networks. In 2020 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI) . IEEE, 1–5
Abdelfatah Hassan, Ismail Shahin, and Mohamed Bader Alsabek. 2020 · 2020
Cited alongside, same era.
Madhurananda Pahar, Marisa Klopper, Robin Warren, and Thomas Niesler. 2020 · 2020
Later among the works it cites.
Contrastive Learning of General-Purpose Audio Representations
Aaqib Saeed, David Grangier, and Neil Zeghidour. 2020 · 2020
Later among the works it cites.
Detecting COVID-19 from Breathing and Coughing Sounds using Deep Neural Networks
Björn W Schuller, Harry Coppock, and Alexander Gaskell. 2020 · 2020
Later among the works it cites.
Coswara-A database of breathing, cough, and voice sounds for COVID-19 diagnosis. In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH , Vol. 2020. International Speech Communication Association, 4811–4815
N Sharma, P Krishnan, R Kumar, S Ramoji, SR Chetupalli, R Nirmala, P Kumar Ghosh, and S Ganapathy. 2020 · 2020
Later among the works it cites.
Hierarchically structured transformer networks for fine-grained spatial event forecasting. In Proceedings of The Web Conference 2020 . 2320–2330
Xian Wu, Chao Huang, Chuxu Zhang, and Nitesh V Chawla. 2020 · 2020
Later among the works it cites.
Robust Detection of COVID-19 in Cough Sounds: Using Recurrence Dynamics and Variable Markov Model
Pauline Mouawad, Tammuz Dubnov, and Shlomo Dubnov. 2021 · 2021
Closest in time.
TERMCast: Temporal Relation Modeling for Effective Urban Flow Forecasting. In Pacific-Asia Conference on Knowledge Discovery and Data Mining
Hao Xue and Flora D Salim. 2021 · 2021
Closest in time.