Yulin Wu

Orcid: 0000-0003-1940-2141

Affiliations:
  • Wuhan University, School of Computer Science, National Engineering Research Center for Multimedia Software, Wuhan, China


According to our database1, Yulin Wu authored at least 13 papers between 2021 and 2025.

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

Timeline

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Bibliography

2025
Multimodal and multichannel speech separation using location-guided speech feature mapping network.
Neurocomputing, 2025

2024
Acoustic scene classification: A comprehensive survey.
Expert Syst. Appl., March, 2024

Adaptive subband partition encoding scheme for multiple audio objects using CNN and residual dense blocks mixture network.
Expert Syst. Appl., 2024

2023
Multi-speaker DoA Estimation Using Audio and Visual Modality.
Neural Process. Lett., December, 2023

Perceptual Audio Object Coding Using Adaptive Subband Grouping with CNN and Residual Block.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2023

Multi-speaker Direction of Arrival Estimation Using Audio and Visual Modalities with Convolutional Neural Network.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2023

2022
High Parameter Frequency Resolution Encoding Scheme for Spatial Audio Objects Using Stacked Sparse Autoencoder.
Neural Process. Lett., 2022

Distortion Reduction via CAE and DenseNet Mixture Network for Low Bitrate Spatial Audio Object Coding.
IEEE Multim., 2022

2021
Audio object coding based on N-step residual compensating.
Multim. Tools Appl., 2021

Stacked Sparse Autoencoder for Audio Object Coding.
Proceedings of the MultiMedia Modeling - 27th International Conference, 2021

Low Bitrates Audio Object Coding Using Convolutional Auto-Encoder and Densenet Mixture Model.
Proceedings of the 2021 IEEE International Conference on Multimedia and Expo, 2021

Efficient Multi-Step Audio Object Coding with Limited Residual Information.
Proceedings of the 2021 IEEE International Conference on Multimedia and Expo, 2021

Spatial Audio Object Coding Based on Time-Frequency Shifting and Scheduling.
Proceedings of the 2021 IEEE International Conference on Multimedia and Expo, 2021


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