Ying Bi

Ying Bi

Professor, Zhengzhou University

Conference Publications

*indicating the corresponding author

  1. Ke Chen, Tianqing Wu, Ying Bi, Jing Liang, Kunjie Yu. Dynamic Threshold Selection in Genetic Programming for Imbalanced Fault Diagnosis. 2025 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2025: 1-8.[http]

  2. Kunjie Yu, Jintao Lian, Ying Bi, Jing Liang. Automatic Feature Learning via Genetic Programming with Flexible Filtering for Skin Cancer Image Classification. 2025 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2025: 1-8.[http]

  3. Jigang Fan, Ying Bi, Bing Xue, Mengjie Zhang. Flexible Region Detection-based Genetic Programming for Fish Classification With Low-Quality Images. 2025 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2025.[http]

  4. Jing Liang, Wenjing Li, Yahui Jia, Ying Bi. A Multitask Genetic Programming Approach with ANew Individual Representation to Symbolic Regression. 2025 International Conference on Electrical Automation and Artificial Intelligence (ICEAAI). IEEE, 2025: 1301-1306.[http]

  5. Jing Liang, Zexuan Yang, Ying Bi. A Two-Stage Approach Combining Feature Selection and Construction for Hyperspectral Crop Classification. 2025 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2025.[http]

  6. Stefano Cagnoni, Ying Bi, Yanan Sun. Evolutionary computation and evolutionary deep learning for image analysis, signal processing and pattern recognition. Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion. 2025.[http]

  7. Caitong Yue, Liming Liu, Jing Liang, Gongping Li,Ying Bi, Mingyuan Yu. (2024, June). Multimodal Multi-Objective Flexible Job Shop Scheduling: A Preliminary Study. In 2024 IEEE Congress on Evolutionary Computation (CEC) (pp. 1-8). IEEE.[http]

  8. Yuefeng Liao, Zhiqiang Wang, Wenjing Li, Ying Bi. A Genetic Programming Approach to Energy Storage Battery State of Charge Estimation. Electrical Artificial Intelligence Conference. Singapore: Springer Nature Singapore, 2024: 402-411[http]

  9. Jiayin Chen, Ya-Hui Jia, Ying Bi, Wei-neng Chen. Generate a Single Heuristic for Multiple Dynamic Flexible Job Shop Scheduling Tasks by Genetic Programming[C].2024 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2024: 1-8.[http]

  10. Jing Liang,Zexuan Yang,Tuo Zhang,Ying Bi. (2024, June). A Two-Stage Approach Using Genetic Algorithm and Genetic Programming for Remote Sensing Crop Classification. In 2024 IEEE Congress on Evolutionary Computation (CEC)(pp 1-8). IEEE.[http]

  11. Qinglan,Ying Bi, Bing Xue, Jane Symonds, Lauren M. Fletcher, Mengjie Zhang. Automatic Quantification of King Salmon Farm Net Occlusion Via Biofouling Detection[C]. 2024 39th International Conference on Image and Vision Computing New Zealand (IVCNZ). IEEE, 2024: 1-6.[http]

  12. Dylon Zeng,Ying Bi,Mengjie Zhang. Genetic Programming-Based Multi-Object Matching for Mussel Floats in Mussel Farm Images[C] 2024 39th International Conference on Image and Vision Computing New Zealand (IVCNZ). IEEE, 2024: 1-6.[http]

  13. Wei-Feng Guo,Yang Li,Chuanqiang Wang,Kunjie Yu,Caitong Yue,Ying Bi. Evolutionary Multitasking Optimization Based Multi-Objective Network Control Principles for Identifying Personalized Drug Targets with Cancer. In 2024 International Conference on New Trends in Computational Intelligence (NTCI)(pp 135-139). IEEE.[http]

  14. Tuo Zhang, Ying Bi, Jing Liang ,Mengjie Zhang . Decomposition-based Multi-objective Genetic Programming for Feature Learning in Image Classification[C].Proceedings of the Genetic and Evolutionary Computation Conference Companion. 2024: 555-558.[http]

  15. Ying Bi ,Mengjie Zhang ,Cagnoni Stefano. Evolutionary Computation and Evolutionary Deep Learning for Image Analysis, Signal Processing and Pattern Recognition[C].Proceedings of the Genetic and Evolutionary Computation Conference Companion. 2024: 1231-1260.[http]

  16. Yi Liu, Ying Bi, Yu Cui, Chengyuan Zhu, Wen Cheng, Mingkai Sheng, Yiding Zhang, Adapting explainable Decision Sets to Continuous-based Real-World Problems, 2024 7th International Symposium on Autonomous Systems (ISAS), 2024

  17. Qinyu Wang, Ying Bi, Bing Xue, Mengjie Zhang, Genetic Programming with Aggregate Channel Features for Flower Localization Using Limited Training Data, International Conference on the Applications of Evolutionary Computation (Part of EvoStar), 2024

  18. Jing Liang, Zhuo Hu, Zong-Wei Li, Ying Bi, Han Cheng, Wei-Feng Guo. A Novel Evolutionary Constrained Multi-Objective Optimization Method for Identifying Personalized Drug Targets Combining with Structural Network Control Principles. Proceedings of the 5th International Conference on Data-driven Optimization of Complex Systems, pp. 1-8, 2023. Best Paper Award

  19. Kangjia Qiao, Jing Liang, Ying Bi, Kunjie Yu, Caitong Yue, Boyang Qu. An Unconstrained Auxiliary Framework for Constrained Many-Objective Optimization. Proceedings of the 5th International Conference on Data-driven Optimization of Complex Systems, pp. 1-8, 2023.

  20. Jing Liang, Xudong Sui, Caitong Yue, Ying Bi, Mingyuan Yu. Differential Evolution Using Interpolation Strategy for Multimodal Multiobjective Optimization. Proceedings of International Symposium on Computer Technology and Information Science, pp. 764-769, 2023.

  21. Dylon Zeng, Ying Bi, Ivy Liu, Bing Xue, Ross Vennell, Mengjie Zhang. A New Genetic Programming-Based Approach to Object Detection in Mussel Farm Images. Proceedings of Image and Vision Computing New Zealand, pp. 1-6, 2023.

  22. Qinglan Fan, Ying Bi, Bing Xue, Mengjie Zhang. Evolving Effective Ensembles for Image Classification Using Multi-objective Multi-tree Genetic Programming. Proceedings of the Australasian Joint Conference on Artificial Intelligence, pp. 1-12, 2022.

  23. Binke Xu, Ying Bi, Bing Xue, Jan Schindler, Brent Martin, and Mengjie Zhang. Automatically Designing U-Nets Using A Genetic Algorithm for Tree Image Segmentation. Proceedings of IEEE SSCI 2022, pp. 1-8, 2022.

  24. Caleb Buchanan, Ying Bi, Bing Xue, Ross Vennell, Simon Childerhouse, Matthew K. Pine, Dana Briscoe, Mengjie Zhang. Deep Convolutional Neural Networks for Detecting Dolphin Echolocation Clicks. Proceedings of Image and Vision Computing New Zealand 2021. 2021, pp. 1-6. (Corresponding Author)

  25. Alistair John McLeay, Abigail McGhie, Dana Briscoe, Ying Bi, Bing Xue, Ross Vennell, Mengjie Zhang. Deep Convolutional Neural Networks with Transfer Learning for Waterline Detection in Mussel Farms. Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI 2021). 2021, pp.1-8. (Corresponding Author)

  26. Zichu Yan, Ying Bi, Bing Xue, Mengjie Zhang. Automatically Extracting Features Using Genetic Programming for Low-Quality Fish Image Classification. Proceedings of IEEE Congress on Evolutionary Computation (CEC 2021). Kraków, Poland (VIRTUAL). 28 June - 1 July 2021. (Corresponding Author) [http]

  27. Qinglan Fan, Ying Bi, Bing Xue, Mengjie Zhang. Genetic Programming with A New Representation and A New Mutation Operator for Image Classification. Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2021). Lille, France. 10-14 July 2021. [http]

  28. Ying Bi, Bing Xue, and Mengjie Zhang. Automatically Extracting Features for Face Classification Using Multi-Objective Genetic Programming. Proceedings of Genetic and Evolutionary Computation Conference Companion. ACM Press. Cancun, Mexico. July 8th-12th 2020, pp 117-118. [http] [pdf]

  29. Ying Bi, Bing Xue, and Mengjie Zhang. Genetic Programming-Based Feature Learning for Facial Expression Classification. Proceedings of IEEE Congress on Evolutionary Computation (CEC 2020). Glasgow, UK, July 19 - 24th 2020. pp 1-8. [http]

  30. Ying Bi, Bing Xue, and Mengjie Zhang. An Automated Ensemble Learning Framework Using Genetic Programming for Image Classification. Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2019). ACM Press. Prague, Czech Republic. 13-17 July 2019. pp 365-373. [http] [pdf]

  31. Ying Bi, Bing Xue, and Mengjie Zhang. An Evolutionary Deep Learning Approach Using Genetic Programming with Convolution Operators for Image Classification. Proceedings of IEEE Congress on Evolutionary Computation (CEC). IEEE Press. Wellington, New Zealand. 10-13 June, 2019. pp. 3197-3204. [http][pdf][Source Code]

  32. Ying Bi, Mengjie Zhang, and Bing Xue. Genetic Programming for Automatic Global and Local Feature Extraction to Image Classification. Proceedings of IEEE Congress on Evolutionary Computation (CEC). IEEE Press. Rio de Janeiro, Brazil. 8-13 July 2018. pp. 1-8. (Nominated for Best Student Paper Award) [http][pdf]

  33. Ying Bi, Mengjie Zhang and Bing Xue. An Automatic Region Detection and Processing Approach in Genetic Programming for Binary Image Classification. Proceedings of the 32nd International Conference on Image and Vision Computing New Zealand (IVCNZ 2017). IEEE Press. Christchurch, New Zealand. 4 - 6 December 2017. pp. 1-6. [http] [pdf]

  34. Yi Wang, Ying Bi, Ting Xie, and Jing Liu. Evaluation of the Comprehensive Strength of the Listed Companies in China’s Cultural Media Industry. Proceedings of 12th International Conference on Service Systems and Service Management (ICSSSM). IEEE Press. Guangzhou, China. 22-24 June 2015. pp. 1-5. [http]

  35. Chen Guo, Zhiwen Guo, Ben Niu, and Ying Bi. A Hybrid Bacterial Foraging Optimization Based on Time-varying Chemotaxis Step and Dynamic Topology Structure. Proceedings of International Conference on Materials, Environmental and Biological Engineering (MEBE 2015). Atlantis Press. Guilin, China. 28-30 March 2015. pp. 587-590. [http]

  36. Ben Niu, Jing Liu, Ying Bi, Ting Xie, and Lijing Tan. Improved Bacterial Foraging Optimization Algorithm with Information Communication Mechanism. Proceedings of Tenth International Conference on Computational Intelligence and Security (CIS). IEEE Press. Kunming, China. 15-16 Nov. 2014. pp. 47-51. [http]

  37. Ben Niu and Ying Bi. Binary Bacterial Foraging Optimization for 0/1 Knapsack Problem. Proceedings of IEEE Congress on Evolutionary Computation (CEC). IEEE Press. Beijing, China. 6-11 July 2014. pp. 647-652. [http]

  38. Hanyang Luo, Jingjing Wang, and Ying Bi. Empirical Research on Consumers’ Intention to Purchase Online. Proceedings of 11th International Conference on Service Systems and Service Management (ICSSSM). IEEE Press. Beijing, China. 25-27 June 2014. pp. 1-5. [http]