Wenfu Wang

Orcid: 0000-0003-1254-3910

According to our database1, Wenfu Wang authored at least 14 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Elastic Knowledge Distillation by Learning From Recollection.
IEEE Trans. Neural Networks Learn. Syst., May, 2023

How do businesses achieve sustainable success and gain a competitive advantage in the green era?
Kybernetes, 2023

Investigating the Mental Workload of Experiencing Virtual Reality on People with Mild Cognitive Impairment.
Proceedings of the Human Aspects of IT for the Aged Population, 2023

2021
SDAPNet: End-to-End Multi-task Simultaneous Detection and Prediction Network.
Proceedings of the International Joint Conference on Neural Networks, 2021

2020
Real-Time Driving Scene Semantic Segmentation.
IEEE Access, 2020

Research on Cognitive Training of Digital Application System Introducing Reminiscence Therapy for the Experience of People with Dementia.
Proceedings of the HCI International 2020 - Late Breaking Papers: Universal Access and Inclusive Design, 2020

2019
A Scoring Method for Driving Safety Credit Using Trajectory Data.
Proceedings of the 2019 IEEE SmartWorld, 2019

2018
A Scoring Method for Driving Safety Credit Using Trajectory Data.
CoRR, 2018

Visual Path Tracking Control for Park Scene.
CoRR, 2018

2017
Combining unidirectional long short-term memory with convolutional output layer for high-performance speech synthesis.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016
First Step Towards End-to-End Parametric TTS Synthesis: Generating Spectral Parameters with Neural Attention.
Proceedings of the Interspeech 2016, 2016

Gating Recurrent Enhanced Memory Neural Networks on Language Identification.
Proceedings of the Interspeech 2016, 2016

End-to-End Language Identification Using Attention-Based Recurrent Neural Networks.
Proceedings of the Interspeech 2016, 2016

Gating recurrent mixture density networks for acoustic modeling in statistical parametric speech synthesis.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016


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