J
Jing Li
Researcher at Chinese Academy of Sciences
Publications - 1606
Citations - 27623
Jing Li is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Medicine & Chemistry. The author has an hindex of 68, co-authored 982 publications receiving 18991 citations. Previous affiliations of Jing Li include Nanchang University & Shandong University.
Papers
More filters
Journal ArticleDOI
A Survey on Deep Learning for Named Entity Recognition
TL;DR: A comprehensive review on existing deep learning techniques for NER is provided in this paper, where the authors systematically categorize existing works based on a taxonomy along three axes: distributed representations for input, context encoder, and tag decoder.
Journal ArticleDOI
A new map of permafrost distribution on the Tibetan Plateau
Defu Zou,Lin Zhao,Yu Sheng,Ji Chen,Guojie Hu,Tonghua Wu,Jichun Wu,Changwei Xie,Xiaodong Wu,Qiangqiang Pang,Wu Wang,Erji Du,Wangping Li,Guangyue Liu,Jing Li,Yanhui Qin,Yongping Qiao,Zhiwei Wang,Jianzong Shi,Guodong Cheng +19 more
TL;DR: In this paper, a new permafrost map based on freezing and thawing indices from modified MODIS land surface temperatures (LSTs) was generated and validated using various ground-based data sets.
Journal ArticleDOI
Error rate performance analysis of coded free-space optical links over gamma-gamma atmospheric turbulence channels
Murat Uysal,Jing Li,Meng Yu +2 more
TL;DR: A pairwise error probability (PEP) expression is derived and the transfer function technique is applied in conjunction with the derived PEP to obtain upper bounds on the bit error rate.
Proceedings ArticleDOI
Wireless diversity through network coding
TL;DR: The results show that network-coded DAS leads to better diversity performance as compared to conventional DAS, at a lower hardware cost and higher spectral efficiency.
Posted Content
A Survey on Deep Learning for Named Entity Recognition
TL;DR: A comprehensive review on existing deep learning techniques for NER, including tagged NER corpora and off-the-shelf NER tools, and systematically categorizes existing works based on a taxonomy along three axes.