Hisashi Uematsu

According to our database1, Hisashi Uematsu authored at least 12 papers between 2013 and 2020.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2020
Sound Event Localization Based on Sound Intensity Vector Refined by Dnn-Based Denoising and Source Separation.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

SPIDERnet: Attention Network For One-Shot Anomaly Detection In Sounds.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Unsupervised Detection of Anomalous Sound Based on Deep Learning and the Neyman-Pearson Lemma.
IEEE ACM Trans. Audio Speech Lang. Process., 2019

DOA Estimation by DNN-based Denoising and Dereverberation from Sound Intensity Vector.
CoRR, 2019

ToyADMOS: A Dataset of Miniature-Machine Operating Sounds for Anomalous Sound Detection.
Proceedings of the 2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2019

SNIPER: Few-shot Learning for Anomaly Detection to Minimize False-negative Rate with Ensured True-positive Rate.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
Efficient Audio Rendering Using Angular Region-Wise Source Enhancement for 360° Video.
IEEE Trans. Multim., 2018

2017
Optimizing acoustic feature extractor for anomalous sound detection based on Neyman-Pearson lemma.
Proceedings of the 25th European Signal Processing Conference, 2017

2016
Binaural sound generation corresponding to omnidirectional video view using angular region-wise source enhancement.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

2014
Real-Time Sound Field Transmission System by Using Wave Field Reconstruction Filter and Its Evaluation.
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2014

2013
Acoustic scene analysis based on latent acoustic topic and event allocation.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2013

User activity estimation method based on probabilistic generative model of acoustic event sequence with user activity and its subordinate categories.
Proceedings of the INTERSPEECH 2013, 2013


  Loading...