Qi Wang
researcher ORCID: 0000-0003-2645-5807
Facts
6 properties- Instance of
- human
- Date of birth
- 1973
- Occupation
- electrical engineer, research fellow
- Employer
- University of Southampton[4]
- Different from
- Q139037296[6]
🏷️ Also known as
en Qi Wang
🔖 Identifiers · 10
- ORCID iD
- 0000-0003-2645-5807
- VIAF cluster ID
- 5269153411883941700004
- GND ID
- 131741632
- DBLP author ID
- 19/1924-2
- DDB person (GND) ID
- 131741632
- Dimensions author ID
- 010107520537.08
- Google Scholar author ID
- b4RsZhUAAAAJ
- IEEE Xplore author ID
- 37085472021
- IdRef ID
- 25033481X
- Web of Science ResearcherID
- B-4907-2015
🔗 Connections
Author of 15
Adaptive Hybrid Precoding for Multiuser Massive MIMO,
An intelligent control of NH3 injection for optimizing the NOx/NH3 ratio in SCR system,
An optimal scaling scheme for DCO-OFDM based visible light communications,
Cross-city transfer learning: Applications and challenges for smart cities and sustainable transportation,
Flexible channel selection mechanism for cognitive radio based last mile smart grid communications,
Improving Needle Tip Tracking and Detection in Ultrasound-Based Navigation System Using Deep Learning-Enabled Approach,
Inferring Emotion from Conversational Voice Data: A Semi-Supervised Multi-Path Generative Neural Network Approach,
Low Cost LSTM Implementation based on Stochastic Computing for Channel State Information Prediction
+7 more
← Authored by 15
Adaptive Hybrid Precoding for Multiuser Massive MIMO,
An intelligent control of NH3 injection for optimizing the NOx/NH3 ratio in SCR system,
An optimal scaling scheme for DCO-OFDM based visible light communications,
Cross-city transfer learning: Applications and challenges for smart cities and sustainable transportation,
Flexible channel selection mechanism for cognitive radio based last mile smart grid communications,
Improving Needle Tip Tracking and Detection in Ultrasound-Based Navigation System Using Deep Learning-Enabled Approach,
Inferring Emotion from Conversational Voice Data: A Semi-Supervised Multi-Path Generative Neural Network Approach,
Low Cost LSTM Implementation based on Stochastic Computing for Channel State Information Prediction
+7 more
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