Journal Articles

*: Corresponding Author, #: Co-First Author.

2023

  1. Kun Qian*, Björn W. Schuller*, Xiaohong Guan*, and Bin Hu*, “Intelligent Music Intervention for Mental Disorders: Insights and Perspectives”, IEEE Transactions on Computational Social Systems (IF-2021: 4.747), vol.10, no.1, pp.2-9, 2023.
  2. Kun Qian, Bin Hu*, Yoshiharu Yamamoto, and Björn W. Schuller, “The Voice of the Body: Why AI Should Listen to it and an Archive”, Cyborg and Bionic Systems, vol.4, no.5, pp.1-3, 2023.
  3. Kun Qian*#, Ruolan Huang#, Zhihao Bao#, Yang Tan, Zhonghao Zhao, Mengkai Sun, Bin Hu*, Björn W. Schuller, and Yoshiharu Yamamoto, “Detecting Somatisation Disorder via Speech: Introducing the Shenzhen Somatisation Speech Corpus”, Intelligent Medicine, in press, pp.1-13, 2023.
  4. Guihua Tian*, Kun Qian*, Xinyi Li, Mengkai Sun, Hao Jiang, Wanyong Qiu, Xiaoming Xie, Zhonghao Zhao, Liangqing Huang, Siyan Luo, Tianxing Guo, Ran Cai, Zhihua Wang, and Björn W. Schuller, “Can a Holistic View Facilitate the Development of Intelligent Traditional Chinese Medicine? A Survey”, IEEE Transactions on Computational Social Systems (IF-2021: 4.747), vol.10, no.2, pp.700-713, 2023.
  5. Zhihua Wang, Kun Qian*, Houguang Liu*, Bin Hu*, Björn W. Schuller, and Yoshiharu Yamamoto,“Exploring Interpretable Representations for Heart Sound Abnormality Detection”, Biomedical Signal Processing and Control (IF-2021: 5.076), vol.82, no.104569, pp.1-12, 2023.
  6. Weijia Liu, Qunxi Dong*, Shuting Sun, Jian, Shen, Kun Qian, and Bin Hu*, “Risk Prediction of Alzheimer’s Disease Conversion in Mild Cognitive Impaired Population based on Brain Age Estimation”, IEEE Transactions on Neural Systems and Rehabilitation Engineering (IF-2021: 4.528), vol.31, pp.2468-2476, 2023.
  7. Jian Shen, Yanan Zhang, Huajian Liang, Zeguang Zhao, Kexin Zhu, Kun Qian, Qunxi Dong, Xiaowei Zhang*, Bin Hu*, “Depression Recognition From EEG Signals Using an Adaptive Channel Fusion Method Via Improved Focal Loss”,IEEE Journal of Biomedical and Health Informatics (IF-2021: 7.021), in press, pp.1-12, 2023.
  8. Jian Shen, Yanan Zhang, Huajian Liang, Zeguang Zhao, Qunxi Dong, Kun Qian, Xiaowei Zhang*, and Bin Hu*, “Exploring the Intrinsic Features of EEG signals via Empirical Mode Decomposition for Depression Recognition“,IEEE Transactions on Neural Systems and Rehabilitation Engineering (IF-2021: 4.528), vol.31, pp.356-365, 2023.

2022

  1. Kun Qian*#, Tomoya Koike#, Toru Nakamura, Björn W. Schuller, and Yoshiharu Yamamoto, “Learning Multimodal Representations for Drowsiness Detection”, IEEE Transactions on Intelligent Transportation Systems (IF-2021: 9.551), vol.23, no.8, pp.11539-11548, 2022.
  2. Björn W. Schuller*, Johanna Löchner*, Kun Qian*, and Bin Hu*, “Digital Mental Health—Breaking a Lance for Prevention”, IEEE Transactions on Computational Social Systems (IF-2021: 4.747), vol.9, no. 6,pp. 1584-1588, 2022.
  3. Bin Hu*, Kun Qian*, Qunxi Dong*, Yuejia Luo*, Yoshiharu Yamamoto*, and Björn W. Schuller*, “Psychological Field Versus Physiological Field: From Qualitative Analysis to Quantitative Modeling of the Mental Status”, IEEE Transactions on Computational Social Systems (IF-2021: 4.747), vol.9, no.5, pp.1275-1281, 2022.
  4. Shuo Liu*, Adria Mallol-Ragolta, Tianhao Yan, Kun Qian*, Emilia Parada-Cabaleiro, Bin Hu*, and Björn W. Schuller, “Capturing Time Dynamics from Speech using Neural Networks for Surgical Masks Detection”, IEEE Journal of Biomedical and Health Informatics (IF-2021: 7.021), vol.26, no.8, pp.4291-4302, 2022.
  5. Shuo Liu*, Adria Mallol-Ragolta, Emilia Parada-Cabeleiro, Kun Qian, Xin Jing, Alexander Kathan, Bin Hu, Björn W. Schuller, “Audio Self-supervised Learning: A Survey”, Patterns, vol.3, issue.12, pp.1-28, 2022.
  6. Bin Hu*, Kun Qian, Ye Zhang, Jian Shen, and Björn W. Schuller,“The Inverse Problems for Computational Psychophysiology: Opinions and Insights”, Cyborg and Bionic Systems, vol.2022, no.9850248, pp.1-3, 2022.
  7. Björn W. Schuller*, Johanna Löchner*, Kun Qian*, and Bin Hu*, “COVID-19’s Impact on Mental Health — The Hour of Computational Aid?”, IEEE Transactions on Computational Social Systems (IF-2021: 4.747), vol.9, no.4, pp.967-973, 2022.
  8. Zhao Ren*, Kun Qian*, Fengquan Dong, Zhenyu Dai, Wolfgang Nejdl, Yoshiharu Yamamoto, and Björn W. Schuller, “Deep Attention-based Neural Networks for Explainable Heart Sound Classification”, Machine Learning with Applications, vol.9, no.100322, pp.1-9, 2022.
  9. Shiliang Zhao*, Jianxin Liu, Yang Tan, and Kun Qian*, “Application of Transient Slope of Zero and Pole in Bode Diagram in Automatic Identification of Filter Parameters”, Journal of Control, Automation and Electrical Systems, pp.1-11, 2022.
  10. Liang Zhang#*, Johann Li#, Ping Li, Xiaoyuan Lu, Maoguo Gong, Peiyi Shen, Guangming Zhu, Syed Afaq Shah, Mohammed Bennarmoun, Kun Qian, and Björn W. Schuller, “MEDAS: An Open-source Platform as an Service to Help Break the Walls between Medicine and Informatics”, Neural Computing and Applications (IF-2021: 5.102), vol.34, pp.6547–6567, 2022.
  11. Bin Hu*, Jian Shen*, Lixian Zhu*, Qunxi Dong*, Hanshu Cai*, and Kun Qian*, “Fundamentals of Computational Psychophysiology: Theory and Methodology”, IEEE Transactions on Computational Social Systems (IF-2021: 4.747), vol.9, no.2, pp.349-355, 2022.

2021

  1. Kun Qian*, Zixing Zhang, Yoshiharu Yamamoto, and Björn W. Schuller, “Artificial Intelligence Internet of Things for the Elderly: From Assisted Living to Health-Care Monitoring”, IEEE Signal Processing Magazine (IF-2021: 15.204), vol.38, no.4, pp.78-88, 2021.
  2. Kun Qian*, Tomoya Koike, Kazuhiro Yoshiuchi, Björn W. Schuller, and Yoshiharu Yamamoto, “Can Appliances Understand the Behaviour of Elderly via Machine Learning? A Feasibility Study”, IEEE Internet of Things Journal (IF-2021: 10.238), vol.8, no.10, pp.8343-8355, 2021.
  3. Kun Qian*#, Maximilian Schmitt#, Huaiyuan Zheng*#, Tomoya Koike#, Jing Han, Juan Liu*, Wei Ji*, Junjun Duan, Meishu Song, Zijiang Yang, Zhao Ren, Shuo Liu, Zixing Zhang, Yoshiharu Yamamoto, and Björn W. Schuller, “Computer Audition for Fighting the SARS-CoV-2 Corona Crisis — Introducing the Multi-task Speech Corpus for COVID-19”, IEEE Internet of Things Journal (IF-2021: 10.238), vol.8, no.21, pp.16035-16046, 2021.
  4. Kun Qian*, Christoph Janott, Maximilian Schmitt, Zixing Zhang, Clemens Heiser, Werner Hemmert, Yoshiharu Yamamoto, and Björn W. Schuller, “Can Machine Learning Assist Locating the Excitation of Snore Sound? A Review”, IEEE Journal of Biomedical and Health Informatics (IF-2021: 7.021), vol.25, no.4, pp.1233-1246, 2021.
  5. Kun Qian*, Liang Zhang, Kezhi Li, and Juan Liu, “Editorial: Machine Learning for Non/Less-Invasive Methods in Health Informatics”, Frontiers in Digital Health, vol.3, pp.1-3, 2021.
  6. Zengjie Zhang, Kun Qian*, Björn W. Schuller, and Dirk Wollherr, “An Online Robot Collision Detection and Identification Scheme by Supervised Learning and Bayesian Decision Theory”, IEEE Transactions on Automation Science and Engineering (IF-2021: 6.636), vol.18, no.3, pp.1144-1156, 2021.
  7. Liang Zhang*#, Kun Qian#, Jun Huang, Mao Liu, and Yasushi Shibuta, “Molecular Dynamics Simulation and Machine Learning of Mechanical Response in Non-equiatomic FeCrNiCoMn High Entropy Alloy”, Journal of Materials Research and Technology (IF-2021: 6.267), vol.13, pp.2043-2054, 2021.
  8. Liang Zhang*#, Kun Qian#, Björn W. Schuller, and Yasushi Shibuta, “Prediction of Mechanical Properties of Non-equiatomic High-entropy Alloy by Atomistic Simulation and Machine Learning”, Metals (IF-2021: 2.695), vol.11, no.6, pp.1-16, 2021.
  9. Zixing Zhang, Ding Liu, Jing Han, Kun Qian*, and Björn W. Schuller, “Learning Audio Sequence Representations for Acoustic Event Classification”, Expert Systems with Applications (IF-2021: 8.665), vol.178, no.115007, pp.1-11, 2021.
  10. Jun Huang*, Linchuan Xu, Kun Qian, Jing Wang, and Kenji Yamanishi, “Multi-Label Learning with Missing and Completely Unobserved Labels”, Data Mining and Knowledge Discovery (IF-2021: 5.406), vol.35, pp.1061-1086, 2021.
  11. Björn W. Schuller*, Dagmar M. Schuller, Kun Qian, Juan Liu, Huaiyuan Zheng, and Xiao Li, “COVID-19 and Computer Audition: An Overview on What Speech & Sound Analysis Could Contribute in the SARS-CoV-2 Corona Crisis”, Frontiers in Digital Health, vol.3, pp.1-10, 2021.

2020

  1. Fengquan Dong#, Kun Qian*#, Zhao Ren*, Alice Baird, Xinjian Li, Zhenyu Dai, Bo Dong, Florian Metze, Yoshiharu Yamamoto, and Björn W. Schuller, “Machine Listening for Heart Status Monitoring: Introducing and Benchmarking HSS–the Heart Sounds Shenzhen Corpus”, IEEE Journal of Biomedical and Health Informatics (IF-2021: 7.021), vol.24, no.7, pp.2082-2092, 2020.
  2. Kun Qian*, Xiao Li, Haifeng Li, Shengchen Li, Wei Li, Zuoliang Ning, Shuai Yu, Limin Hou, Gang Tang, Jing Lu, Feng Li, Shufei Duan, Chengcheng Du, Yao Cheng, Yujun Wang, Lin Gan, Yoshiharu Yamamoto, and Björn W. Schuller, “Computer Audition for Healthcare: Opportunities and Challenges”, Frontiers in Digital Health, vol.2, pp.1-4, 2020.
  3. Kun Qian*, Fengquan Dong, Zhao Ren, Zhenyu Dai, Bo Dong, and Björn W. Schuller, “Opportunities and Challenges for Heart Sound Recognition: A Brief on the Heart Sounds Shenzhen Corpus” (in Chinese), Journal of Fudan University (Natural Science), vol.59. no.3, pp.354-359.
  4. Yu Qiao, Kun Qian, and Ziping Zhao*, “Bird Sound Recognition based on Machine Listening: A Survey on Chinese Literature” (in Chinese), Journal of Fudan University (Natural Science), vol.59. no.3, pp.375-380.
  5. Zixing Zhang*, Jing Han, Kun Qian, Christoph Janott, Yanan Guo, and Björn W. Schuller, “Snore-GANs: Improving Automatic Snore Sound Classification with Synthesized Data”, IEEE Journal of Biomedical and Health Informatics (IF-2021: 7.021), vol.24, no.1, pp.300-310, 2020.
  6. Maria Littmann*#, Katharina Selig*#, Liel Cohen-Lavi, Yotam Frank, Peter Hönigschmid, Evans Kataka, Anja Mösch, Kun Qian, Avihai Ron, Sebastian Schmid, Adam Sorbie, Liran Szlak, Ayana Dagan-Wiener, Nir Ben-Tal, Masha Y. Niv, Daniel Razansky, Björn W. Schuller, Donna Ankerst, Tomer Hertz, and Burkhard Rost, “Validity of Machine Learning in Biology and Medicine Increased Through Collaborations Across Fields of Expertise”, Nature Machine Intelligence (IF-2021: 25.898), vol.2, January, pp.18-24, 2020.

2019

  1. Kun Qian*, Maximilian Schmitt, Christoph Janott, Zixing Zhang, Clemens Heiser, Winfried Hohenhorst, Michael Herzog, Werner Hemmert, and Björn W. Schuller, “A Bag of Wavelet Features for Snore Sound Classification”, Annals of Biomedical Engineering (IF-2021: 4.219), vol.47, no.4, pp.1000-1011, 2019.

2018

  1. Kun Qian*, Christoph Janott, Zixing Zhang, Jun Deng, Clemens Heiser, Winfried Hohenhorst, Michael Herzog, Werner Hemmert, and Björn W. Schuller, “Teaching Machines on Snoring: A Benchmark on Computer Audition for Snore Sound Excitation Localisation”, Archives of Acoustics (IF-2021: 1.043), vol.43, no.3, pp.465-475, 2018.
  2. Zhao Ren*, Kun Qian, Zixing Zhang, Vedhas Pandit, Alice Baird, and Björn W. Schuller, “Deep Scalogram Representations for Acoustic Scene Classification”, IEEE/CAA Journal of Automatica Sinica (IF-2021: 7.847), vol.5, no.3, pp.662-669, 2018.
  3. Christoph Janott*, Maximilian Schmitt, Yue Zhang, Kun Qian, Vedhas Pandit, Zixing Zhang, Clemens Heiser, Winfried Hohenhorst, Michael Herzog, Werner Hemmert, and Björn W. Schuller, “Snoring Classified: The Munich Passau Snore Sound Corpus”, Computers in Biology and Medicine (IF-2021: 6.698), vol.94, pp.106-118, 2018.

2017

  1. Kun Qian*, Zixing Zhang, Alice Baird, and Björn W. Schuller, “Active Learning for Bird Sound Classification via a Kernel-based Extreme Learning Machine”, Journal of the Acoustical Society of America (IF-2021: 2.482), vol.142, no.4, pp.1796-1804, 2017.
  2. Kun Qian*, Christoph Janott, Vedhas Pandit, Zixing Zhang, Clemens Heiser, Winfried Hohenhorst, Michael Herzog, Werner Hemmert, and Björn W. Schuller, “Classification of the Excitation Location of Snore Sounds in the Upper Airway by Acoustic Multi-Feature Analysis”, IEEE Transactions on Biomedical Engineering (IF-2021: 4.756), vol.64, no.8, pp.1731-1741, 2017.
  3. Kun Qian*, Jian Guo, Ken Ishida, and Satoshi Matsuoka, “Fast Recognition of Bird Sounds Using Extreme Learning Machines”, IEEJ Transactions on Electrical and Electronic Engineering (IF-2021: 0.923), vol.12, no.2, pp.294-296, 2017.
  4. Kun Qian*, Zixing Zhang, Alice Baird, and Björn W. Schuller, “Active Learning for Bird Sounds Classification”, Acta Acustica (IF-2021: 0.960), vol.103, no.3, pp.361-364, 2017.
  5. Jian Guo, Kun Qian, Gongxuan Zhang*, Huijie Xu, and Björn W. Schuller, “Accelerating Biomedical Signal Processing Using GPU: A Case Study of Snore Sounds Feature Extraction”, Interdisciplinary Sciences: Computational Life Sciences (IF-2021: 3.492), vol.9, no.4, pp.550-555, 2017.

2015

  1. Kun Qian, Zhiyong Xu*, Huijie Xu, Yaqi Wu, and Zhao Zhao, “Automatic Detection, Segmentation and Classification of Snore Related Signals from Overnight Audio Recording”, IET Signal Processing (IF-2021: 1.819), vol.9, no.1, pp.21-29, 2015.

2014

  1. Kun Qian*#, Jian Guo#, Huijie Xu*, Zhaomeng Zhu, and Gongxuan Zhang, “Snore Related Signals Processing in a Private Cloud Computing System”, Interdisciplinary Sciences: Computational Life Sciences (IF-2021: 3.492), vol.6, no.3, pp.216-221, 2014.
  2. Yuzhuo Fang, Zhiyong Xu*, Guang Cheng, and Kun Qian, “Direction Estimation of Microphone Array Direct Wave based on Adaptive Blind Identication” (in Chinese), Journal of Nanjing University of Science and Technology, vol.38, no.2, pp.264-270, 2014.

2013

  1. Kun Qian, Yuzhuo Fang, Zhiyong Xu*, and Huijie Xu*, “Comparison of Two Acoustic Features for Classification of Different Snore Signals”, Chinese Journal of Electron Devices, vol.36, no.4, pp.455-459, 2013.