汕头大学主页|汕头大学工学院|English Vision
  联系信息

邮件:zfan@stu.edu.cn

地址:广东省汕头市大学路243号汕头大学科学楼

邮编:515063

 
科研成果
2018年代表性论文
 
发布时间:2019/1/1 10:54:10
  1. X. Cai, Z. Mei, Z. Fan, and Q. Zhang, “A constrained decomposition approach with grids for evolutionary multi-objective optimization,” IEEE Transactions on Evolutionary Computation, vol. 22, no. 4, pp.564–577, 2018. (SCI人工智能1区, IF:10.629)Download PDF
  2. X. Cai, Z. Mei, and Z. Fan, “A decomposition-based many-objective evolutionary algorithm with two types of adjustments for direction,” IEEE Transactions on Cybernetics, vol. 48, no. 8, pp. 2335–2348, 2018. (SCI人工智能1区,IF:8.803)Download PDF
  3. X. Cai, H. Sun, and Z. Fan, “A diversity indicator based on reference vectors for many-objective optimization,” Information Sciences, vol. 430, pp. 467–486, 2018. (SCI自动控制系统1区,IF:4.832)Download PDF
  4. Z. Fan, Y. Rong, X. Cai, J. Lu, W. Li, H. Lin, and X. Chen, “Optic disk detection in fundus image based on structured learning,” IEEE Journal of Biomedical and Health Informatics, vol. 22, no. 1, pp. 224–234, 2018. (SCI信息系统1区,IF:3.850)Download PDF
  5. Z. Fan, J. Lu, M. Gong, H. Xie, and E. D. Goodman, “Automatic tobacco plant detection in UAV images via deep neural networks,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 3, pp. 876–887, 2018. (SCI电子与电气2区,IF:3.026)Download PDF
  6. Y. Rong, D. Xiang, W. Zhu, K. Yu, F. Shi, Z. Fan, and X. Chen, “Surrogate-assisted retinal OCT image classification based on convolutional neural networks,” IEEE Journal of Biomedical and Health Informatics, 2018. (SCI信息系统1区,IF:3.850)Download PDF
  7. H. Huang, S. Ye, Z. Fan, Z. Lin, L. Lv, and Z. Hao, “Evolutionary programming with a simulated-conformist mutation strategy,” Soft Computing, vol. 22, no. 2, pp. 659–676, 2018. (SCI人工智能2区,IF:2.472)Download PDF
  8. T. Yang, Y. Chen, and Z. Fan*, “Vegetation segmentation based on variational level set using multi-channel local wavelet texture and color,” Signal, Image and Video Processing, pp. 1–8, 2018. (SCI电子与电气3区,IF:1.643)Download PDF
  9. Y. Rong, K. Yu, D. Xiang, W. Zhu, Z. Fan, and X. Chen, “Explaining convolutional neural networks for area estimation of choroidal neovascularization via genetic programming,” in Computational Pathology and Ophthalmic Medical Image Analysis. Springer, https://doi.org/10.1007/978-3-030-00949-6_25, 2018, pp. 210–218.
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