Publications

Please see the full list of her publications in Google Scholar.

Selected Publications

Book Chapters

• N. Cummins, Z. Ren, A. Mallol-Ragolta, and B. Schuller, Artificial Intelligence in Precision Health, ch. Chapter 5 – Machine learning in digital health, recent trends, and ongoing challenges, pp. 121–148. Elsevier, 2020

Journal Articles

• Z. Ren, Y. Chang, W. Nejdl, and B. Schuller, “Learning complementary representations via attention-based ensemble learning for cough-based COVID-19 recognition,” Acta Acustica, 2022. 4 pages, to appear

• Z. Ren, Y. Chang, K. D. Bartl-Pokorny, F. B. Pokorny, and B. Schuller, “The acoustic dissection of cough: Diving into machine listening-based COVID-19 analysis and detection,” Journal of Voice, 2022. to appear

• Y. Chang, X. Jing, Z. Ren, and B. Schuller, “CovNet: A transfer learning framework for automatic COVID-19 detection from crowd-sourced cough sounds,” Frontiers in Digital Health, vol. 3, pp. 1–11, Jan. 2022 [code]

• Z. Ren, Q. Kong, J. Han, M. Plumbley, and B. Schuller, “CAA-Net: Conditional atrous CNNs with attention for explainable device-robust acoustic scene classification,” IEEE Transactions on Multimedia, Nov. 2020. 12 pages [code]

• F. Dong, K. Qian, Z. Ren, A. Baird, X. Li, Z. Dai, B. Dong, F. Metze, Y. Yamamoto, and B. Schuller, “Machine listening for heart status monitoring: Introducing and benchmarking HSS – the heart sounds Shenzhen corpus,” IEEE Journal of Biomedical and Health Informatics, vol. 24, pp. 2082–2092, Nov. 2019

• Z. Ren, K. Qian, Z. Zhang, V. Pandit, A. Baird, and B. Schuller, “Deep scalogram representations for acoustic scene classification,” IEEE/CAA Journal of Automatica Sinica, vol. 5, pp. 662–669, May 2018

Conference Papers

• Y. Chang, Z. Ren, T. T. Nguyen, W. Nejdl, and B. Schuller, “Example-based explanations with adversarial attacks for respiratory sound analysis,” in Proc. INTERPSEECH, (Incheon, Korea), 2022. to appear [code]

• Z. Ren, T. T. Nguyen, and W. Nejdl, “Prototype learning for interpretable respiratory sound analysis,” in Proc. ICASSP, (Singapore), pp. 9087–9091, 2022 [code]

• Z. Ren, J. Han, N. Cummins, and B. Schuller, “Enhancing transferability of black-box adversarial attacks via lifelong learning for speech emotion recognition models,” in Proc. INTERSPEECH, (Shanghai, China), pp. 496–500, 2020

• Z. Ren, A. Baird, J. Han, Z. Zhang, and B. Schuller, “Generating and protecting against adversarial attacks for deep speech-based emotion recognition models,” in Proc. ICASSP, (Barcelona, Spain), pp. 7184–7188, 2020 [code]

• Z. Ren, J. Han, N. Cummins, Q. Kong, M. Plumbley, and B. Schuller, “Multi-instance learning for bipolar disorder diagnosis using weakly labelled speech data,” in Proc. DPH, (Marseille, France), pp. 79–83, 2019

• F. Ringeval, B. Schuller, M. Valstar, N. Cummins, R. Cowie, L. Tavabi, M. Schmitt, S. Alisamir, S. Amiriparian, E.-M. Messner, S. Song, S. Liu, Z. Zhao, A. Mallol-Ragolta, Z. Ren, M. Soleymani, and M. Pantic, “AVEC 2019 workshop and challenge: State-of-mind, detecting depression with AI, and cross-cultural affect recognition,” in Proc. AVEC, (Nice, France), pp. 3–12, 2019

• Z. Ren, Q. Kong, J. Han, M. Plumbley, and B. Schuller, “Attention-based atrous convolutional neural networks: Visualisation and understanding perspectives of acoustic scenes,” in Proc. ICASSP, (Brighton, UK), pp. 56–60, 2019 [code]

• Z. Ren, Q. Kong, K. Qian, M. Plumbley, and B. Schuller, “Attention-based convolutional neural networks for acoustic scene classification,” in Proc. DCASE, (Surrey, UK), pp. 39–43, 2018

• Z. Ren, N. Cummins, J. Han, S. Schnieder, J. Krajewski, and B. Schuller, “Evaluation of the pain level from speech: Introducing a novel pain database and benchmarks,” in Proc. ITG, (Oldenburg, Germany), pp. 56–60, 2018

• B. Schuller, S. Steidl, A. Batliner, P. Marschik, H. Baumeister, F. Dong, S. Hantke, F. Pokorny, E.-M. Rathner, K. Bartl-Pokorny, C. Einspieler, D. Zhang, A. Baird, S. Amiriparian, K. Qian, Z. Ren, M. Schmitt, P. Tzirakis, and S. Zafeiriou, “The INTERSPEECH 2018 computational paralinguistics challenge: Atypical & self-assessed affect, crying & heart beats,” in Proc. INTERSPEECH, (Hyderbad, India), pp. 122–126, 2018

• Z. Ren, N. Cummins, V. Pandit, J. Han, K. Qian, and B. Schuller, “Learning image-based representations for heart sound classification,” in Proc. DH, (Lyon, France), pp. 143–147, 2018

• Z. Ren, V. Pandit, K. Qian, Z. Yang, Z. Zhang, and B. Schuller, “Deep sequential image features on acoustic scene classification,” in Proc. DCASE, (Munich, Germany), pp. 113–117, 2017

• Z. Ren, Q. Zhang, H. Zhu, and Q. Wang, “Extending the FOV from disparity and color consistencies in multiview light fields,” in Proc. ICIP, (Beijing, China), pp. 1157–1161, 2017

Patents

• Qing Wang, Zhao Ren, Guoqing Zhou, Wang Zeng, “Light field acquisition device based on micro camera array and data processing method (基于微相机阵列的光场采集装置及数据处理方法)”, No. CN106027861A, Oct. 2016.

• Qing Wang, Zhe Ji, Shu Han, Chunping Zhang, Zhao Ren, Guoqing Zhou, “An equipment and algorithms for light field camera extrinsic parameters calibration (光场相机外参数标定装置及方法)”, No. CN105654484A, June 2016.