王帅


男,山东济宁人,博士,讲师。2021年6月毕业于中国科学院大学计算机应用技术专业,获工学博士学位。主要研究方向为计算机视觉、产品表面缺陷检测。

科研方面,先后在《小型微型计算机系统》、《ICICTA》、《ICCC》、《Metals》、等国内外期刊会议发表论文5篇,其中SCI检索1篇,EI检索3篇。

主要学术成果:

[1]Automatic Detection and Classification of Steel Surface Defect Using Deep Convolutional Neural Networks. Metals. 2021; 11(3):388.(SCI)

[2]RGBD saliency object detection via regional feature clustering [C]. The 12th International Conference on Intelligent Computation Technology and Automation, ICICTA 2019.(EI)

[3]Surface Defect Detection Using U-net and transfer learning [C]. The 13th International Conference on Intelligent Computation Technology and Automation, ICICTA 2020.(EI)

[4]Steel Surface Defect Detection Using Transfer Learning and Image Segmentation [C]. 2020 IEEE 6th International Conference on Computer and Communications (ICCC), Chengdu, China, 2020, pp. 420-425.(EI)

[5]基于区域特征聚类的RGBD显著性物体检测[J].小型微型计算机系统, 2019, 40(4): 704-709.

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