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Yong Xu

44 papers hereh-index 376.1k citations85 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author9
  • middle author33
  • last author1

Across the 43 of 44 papers where every author was matched, so the position is known.

fields
  • cs.SD22
  • eess.AS20
  • cs.CV1
  • cs.LG1
same name
  • Yong Xu — 87 papers, h 50
  • Yong Xu — 36 papers, h 26
  • Yong Xu — 30 papers, h 34
  • Yong Xu — 21 papers, h 43
  • Yong Xu — 16 papers, h 68
  • Yong Xu — 15 papers, h 12

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20162022
most citedMulti-modal Multi-channel Target Speech Separation

111 citations · 781 across the 43 of their papers we have counts for

collaborators
Showing 2016Show all

4 papers · 1 filter

cs.SD2016

A Joint Detection-Classification Model for Audio Tagging of Weakly Labelled Data

Qiuqiang Kong, Yong Xu, Wenwu Wang +1

Audio tagging aims to assign one or several tags to an audio clip. Most of the datasets are weakly labelled, which means only the tags of the clip are known, without knowing the oc…

cs.SD2016★ 21 cited

Hierarchical learning for DNN-based acoustic scene classification

Yong Xu, Qiang Huang, Wenwu Wang +1

In this paper, we present a deep neural network (DNN)-based acoustic scene classification framework. Two hierarchical learning methods are proposed to improve the DNN baseline perf…

cs.SD2016★ 86 cited

Unsupervised Feature Learning Based on Deep Models for Environmental Audio Tagging

Yong Xu, Qiang Huang, Wenwu Wang +4

Environmental audio tagging aims to predict only the presence or absence of certain acoustic events in the interested acoustic scene. In this paper we make contributions to audio t…

cs.CV2016★ 12 cited

Fully DNN-based Multi-label regression for audio tagging

Yong Xu, Qiang Huang, Wenwu Wang +2

Acoustic event detection for content analysis in most cases relies on lots of labeled data. However, manually annotating data is a time-consuming task, which thus makes few annotat…

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