World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
9725
World Ranking
6447
National Ranking
858

Overview

Jun Du is affiliated with the University of Science and Technology of China. Their primary field of study is Computer Science, with significant contributions across several subfields including Signal Processing, Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mechanics, and Surgery.

Their research spans multiple specialized topics, notably:

  • Speech and Audio Processing
  • Speech Recognition and Synthesis
  • Handwritten Text Recognition Techniques
  • Music and Audio Processing
  • Advanced Adaptive Filtering Techniques
  • Natural Language Processing Techniques
  • Image Processing and 3D Reconstruction

Jun Du has authored publications in several frequent venues. These include:

  • arXiv (Cornell University)
  • IEEE/ACM Transactions on Audio Speech and Language Processing
  • Pattern Recognition
  • SSRN Electronic Journal
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Recent papers highlight the diversity and interdisciplinary nature of their research work:

  • TextMountain: Accurate scene text detection via instance segmentation, 2020, Pattern Recognition
  • A Four-Stage Data Augmentation Approach to ResNet-Conformer Based Acoustic Modeling for Sound Event Localization and Detection, 2023, IEEE/ACM Transactions on Audio Speech and Language Processing
  • Radical analysis network for learning hierarchies of Chinese characters, 2020, Pattern Recognition
  • Information Fusion in Attention Networks Using Adaptive and Multi-Level Factorized Bilinear Pooling for Audio-Visual Emotion Recognition, 2021, IEEE/ACM Transactions on Audio Speech and Language Processing
  • Split, Embed and Merge: An accurate table structure recognizer, 2022, Pattern Recognition

Collaborations are also a significant part of Jun Du's academic activity. Their frequent co-authors include:

  • Chin-Hui Lee
  • Jianshu Zhang
  • Qing Wang
  • Shutong Niu
  • Jiefeng Ma

Best Publications

  • A regression approach to speech enhancement based on deep neural networks

    Yong Xu;Jun Du;Li-Rong Dai;Chin-Hui Lee

  • An Experimental Study on Speech Enhancement Based on Deep Neural Networks

    Yong Xu;Jun Du;Li-Rong Dai;Chin-Hui Lee

  • On Mean Absolute Error for Deep Neural Network Based Vector-to-Vector Regression

    Jun Qi;Jun Du;Sabato Marco Siniscalchi;Xiaoli Ma

  • Watch, attend and parse: An end-to-end neural network based approach to handwritten mathematical expression recognition

    Jianshu Zhang;Jun Du;Shiliang Zhang;Dan Liu

  • Multiple-target deep learning for LSTM-RNN based speech enhancement

    Lei Sun;Jun Du;Li-Rong Dai;Chin-Hui Lee

  • Multi-Agent Reinforcement Learning Aided Intelligent UAV Swarm for Target Tracking

    Zhaoyue Xia;Jun Du;Jingjing Wang;Chunxiao Jiang

  • The Second DIHARD Diarization Challenge: Dataset, Task, and Baselines.

    Neville Ryant;Kenneth Church;Christopher Cieri;Alejandrina Cristià

  • Multi-Scale Attention with Dense Encoder for Handwritten Mathematical Expression Recognition

    Jianshu Zhang;Jun Du;Lirong Dai

  • SDN-based Resource Allocation in Edge and Cloud Computing Systems: An Evolutionary Stackelberg Differential Game Approach.

    Jun Du;Chunxiao Jiang;Abderrahim Benslimane;Song Guo

  • Stochastic Optimization Aided Energy-Efficient Information Collection in Internet of Underwater Things Networks

    Zhengru Fang;Jingjing Wang;Jun Du;Xiangwang Hou

  • Robust speech recognition with speech enhanced deep neural networks.

    Jun Du;Qing Wang;Tian Gao;Yong Xu

  • A Four-Stage Data Augmentation Approach to ResNet-Conformer Based Acoustic Modeling for Sound Event Localization and Detection

    Unknown

  • Track, Attend, and Parse (TAP): An End-to-End Framework for Online Handwritten Mathematical Expression Recognition

    Jianshu Zhang;Jun Du;Lirong Dai

  • TextMountain: Accurate scene text detection via instance segmentation

    Yixing Zhu;Jun Du

  • Multi-objective learning and mask-based post-processing for deep neural network based speech enhancement.

    Yong Xu;Jun Du;Zhen Huang;Li-Rong Dai

  • A speech enhancement approach using piecewise linear approximation of an explicit model of environmental distortions.

    Jun Du;Qiang Huo

  • Attention Based Fully Convolutional Network for Speech Emotion Recognition

    Yuanyuan Zhang;Jun Du;Zirui Wang;Jianshu Zhang

  • Dynamic noise aware training for speech enhancement based on deep neural networks.

    Yong Xu;Jun Du;Li-Rong Dai;Chin-Hui Lee

  • A regression approach to single-channel speech separation via high-resolution deep neural networks

    Jun Du;Yanhui Tu;Li-Rong Dai;Chin-Hui Lee

  • The Third DIHARD Diarization Challenge

    Neville Ryant;Prachi Singh;Venkat Krishnamohan;Rajat Varma

  • SNR-Based Progressive Learning of Deep Neural Network for Speech Enhancement.

    Tian Gao;Jun Du;Li-Rong Dai;Chin-Hui Lee

  • First DIHARD Challenge Evaluation Plan

    Neville Ryant;Kenneth Church;Christopher Cieri;Alejandrina Cristia

  • Attention Based Fully Convolutional Network for Speech Emotion Recognition

    Yuanyuan Zhang;Jun Du;Zirui Wang;Jianshu Zhang

Frequent Co-Authors

Chin-Hui Lee
Chin-Hui Lee Georgia Institute of Technology
Li-Rong Dai
Li-Rong Dai University of Science and Technology of China
Yong Ren
Yong Ren Tsinghua University
Chunxiao Jiang
Chunxiao Jiang Tsinghua University
Mark Liberman
Mark Liberman University of Pennsylvania
Kenneth Church
Kenneth Church Baidu (China)
Frank K. Soong
Frank K. Soong Microsoft Research Asia (China)
Zhen-Hua Ling
Zhen-Hua Ling University of Science and Technology of China
Shui Yu
Shui Yu University of Technology Sydney
Zhu Han
Zhu Han University of Houston

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