宋新航 - 中国科学院计算技术研究所 -

个人简介

2019年9月—今：中科院计算所，副研究员 2017年6月—2019年8月：中科院计算所，博士后 2011年7月—2017年7月：中国科学院大学，博士 2007年9月—2011年7月：北京交通大学，计算机与信息技术学院，学士

研究领域

场景识别与理解

近期论文

查看导师最新文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

Xinhang Song, Shuqiang Jiang, Luis Herranz, Chengpeng Chen, "Learning Effective RGB-D Representations for Scene Recognition," IEEE Transactions on Image Processing (TIP), 28(2): 980-993 (2019), CCF A, IF:6.79 Xinhang Song, Shuqiang Jiang, Bohan Wang, Chengpeng Chen, Gongwei Chen. “Image Representations with Spatial Object-to-Object Relations for RGB-D Scene Recognition.” IEEE Transactions on Image Processing (TIP), 29: 525-537 (2020), CCF A, IF:6.79 Xinhang Song, Shuqiang Jiang, Luis Herranz. “Multi-scale multi-feature context modeling for scene recognition in the semantic manifold.” IEEE Transactions on Image Processing (TIP), 2017, CCF A, IF:6.79 Xinhang Song, Shuqiang Jiang, Luis Herranz, Yan Kong, Kai Zheng, “Category co-occurrence modeling for large scale scene recognition”, Pattern Recognition (PR) 59: 98-111 (2016) , CCF B, IF: 5.898 Xinhang Song, Sixian Zhang, Yuyun Hua and Shuqiang Jiang. “Aberrance-aware gradient-sensitive attentions for scene recognition with RGB-D videos.” (ACM Multimedia 2019), 21-25 October 2019, Nice, France , CCF A Xinhang Song, Bohan Wang, Gongwei Chen and Shuqiang Jiang. “MUCH: MUtual Coupling enHancement of scene recognition and dense captioning.” (ACM Multimedia 2019), 21-25 October 2019, Nice, France , CCF A Xinhang Song, chengpeng chen, Shuqiang Jiang. “RGB-D Scene Recognition with Object-to-Object Relation” The 25th ACM Multimedia Conference (ACM Multimedia 2017), CCF A Xinhang Song, Shuqiang Jiang, Luis Herranz. “Combining Models from Multiple Sources for RGB-D Scene Recognition” The 26th International Joint Conference on Artificial Intelligence (IJCAI) 2017, CCF A Xinhang Song, Luis Herranz, Shuqiang Jiang. “Depth CNNs for RGB-D scene recognition: learning from scratch better than transferring from RGB-CNNs” AAAI, 2017, CCF A Xinhang Song, Shuqiang Jiang, Luis Herranz. “Joint Multi-feature Spatial Context for Scene Recognition in the Semantic Manifold.” IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2015: 1312-1320, CCF A