Yang Bing

熟练java、python、数据库、人工智能等，做过多次前端和后端开发，目前已经发表过两篇顶刊论文（计算机视觉相关）以及多篇SCI论文。目前的研究方向主要是计算机视觉、自然语言处理、进化算法等。
主要研究成果：
1、Yang B, Kang Y, Zhang L, et al. GGAC: Multi-relational image gated GCN with attention convolutional binary neural tree for identifying disease with chest X-rays[J]. Pattern Recognition, 2021, 120: 108113.
2、Yang B, Kang Y, Yuan Y Y, et al. ST-LBAGAN: Spatio-temporal learnable bidirectional attention generative adversarial networks for missing traffic data imputation[J]. Knowledge-Based Systems, 2021, 215: 106705.
3、Kang Y, Yang B, Zhang L, et al. ST-IFC: efficient spatial-temporal inception fully connected network for citywide crowd flow prediction[J]. International Journal of Sensor Networks, 2021, 35(1): 23-31.
4、Yang B, Kang Y, Yuan Y, et al. ST-FVGAN: filling series traffic missing values with generative adversarial network[J]. Transportation Letters, 2021: 1-9.
5、Yang B, Kang Y, Li H, et al. Spatio-temporal expand-and-squeeze networks for crowd flow prediction in metro