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Shuhui Qu
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Year
Very deep convolutional neural networks for raw waveforms
W Dai, C Dai, S Qu, J Li, S Das
2017 IEEE international conference on acoustics, speech and signal …, 2017
3442017
A comparison of deep learning methods for environmental sound detection
J Li, W Dai, F Metze, S Qu, S Das
2017 IEEE International conference on acoustics, speech and signal …, 2017
1292017
A comparison of deep learning methods for environmental sound detection
J Li, W Dai, F Metze, S Qu, S Das
2017 IEEE International conference on acoustics, speech and signal …, 2017
1292017
Optimized adaptive scheduling of a manufacturing process system with multi-skill workforce and multiple machine types: An ontology-based, multi-agent reinforcement learning …
S Qu, J Wang, S Govil, JO Leckie
Procedia Cirp 57, 55-60, 2016
702016
Adversarial music: Real world audio adversary against wake-word detection system
J Li, S Qu, X Li, J Szurley, JZ Kolter, F Metze
Advances in Neural Information Processing Systems 32, 2019
472019
A centralized reinforcement learning approach for proactive scheduling in manufacturing
S Qu, T Chu, J Wang, J Leckie, W Jian
2015 IEEE 20th Conference on Emerging Technologies & Factory Automation …, 2015
382015
Large-scale traffic grid signal control with regional reinforcement learning
T Chu, S Qu, J Wang
2016 american control conference (acc), 815-820, 2016
322016
Learning adaptive dispatching rules for a manufacturing process system by using reinforcement learning approach
S Qu, J Wang, G Shivani
2016 IEEE 21st International Conference on Emerging Technologies and Factory …, 2016
262016
Let blind people see: real-time visual recognition with results converted to 3D audio
R Jiang, Q Lin, S Qu
Report No. 218, Standord University, Stanford, USA, 2016
252016
Comuptional reasoning and learning for smart manufacturing under realistic conditions
S Qu, R Jian, T Chu, J Wang, T Tan
2014 International Conference on Behavioral, Economic, and Socio-Cultural …, 2014
212014
Online identification of inertia distribution in normal operating power system
F Zeng, J Zhang, Y Zhou, S Qu
IEEE Transactions on Power Systems 35 (4), 3301-3304, 2020
172020
Understanding audio pattern using convolutional neural network from raw waveforms
S Qu, J Li, W Dai, S Das
arXiv preprint arXiv:1611.09524, 2016
172016
A comparison of deep learning methods for environmental sound
J Li, W Dai, F Metze, S Qu, S Das
arXiv preprint arXiv:1703.06902, 2017
142017
Dynamic scheduling in large-scale stochastic processing networks for demand-driven manufacturing using distributed reinforcement learning
S Qu, J Wang, J Jasperneite
2018 IEEE 23rd International Conference on Emerging Technologies and Factory …, 2018
122018
Sound event detection for real life audio DCASE challenge
JL Dai Wei, P Pham, S Das, S Qu, F Metze
Proc. Workshop Detection and Classification of Acoustic Scenes and Events, 2016
122016
Large-scale multi-agent reinforcement learning using image-based state representation
T Chu, S Qu, J Wang
2016 IEEE 55th Conference on Decision and Control (CDC), 7592-7597, 2016
102016
Real-time decision support with reinforcement learning for dynamic flowshop scheduling
J Wang, S Qu, J Wang, JO Leckie, R Xu
Smart SysTech 2017; European Conference on Smart Objects, Systems and …, 2017
82017
Acoustic scene recognition with deep neural networks (DCASE challenge 2016)
W Dai, J Li, P Pham, S Das, S Qu
Tech. Rep., DCASE2016 Challenge, 2016
82016
Acoustic scene recognition with deep neural networks (DCASE challenge 2016)
JL Dai Wei, P Pham, S Das, S Qu
Robert Bosch Research and Technology Center 3, 2016
82016
Audio-visual event recognition through the lens of adversary
JB Li, K Ma, S Qu, PY Huang, F Metze
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
62021
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