Ting Lei

Oct 23, 2024 | pubs.acs.org | Jun Huang |Ting Lei |Qi Zhou |Zhou Fang

Oct 23, 2024 | dx.doi.org | Jun Huang |Ting Lei |Qi Zhou |Zhou Fang

Dec 31, 2023 | mdpi.com | Zhen Lei |Ting Lei |T. L

1. IntroductionSpatial data conflation is the process of combining two maps to produce an improved map. It involves matching the geospatial features in two map datasets that represent the same objects in reality and possibly merging their attributes and geometries. Conflation is needed in many geospatial analytical tasks, including transportation research.

Oct 13, 2023 | nature.com | Meifang Lin |Qian Zhou |Ting Lei |Ning Shang |Qiao Zheng |Nan Wang

AbstractCongenital malformations of the central nervous system are among the most common major congenital malformations. Deep learning systems have come to the fore in prenatal diagnosis of congenital malformation, but the impact of deep learning-assisted detection of congenital intracranial malformations from fetal neurosonographic images has not been evaluated.

May 14, 2023 | onlinelibrary.wiley.com | Ting Lei |Zhen Lei

Abstract Geospatial data conflation is the process of combining multiple datasets about a geographic phenomenon to produce a single, richer dataset. It has received increased research attention due to its many applications in map making, transportation, planning, and temporal geospatial analyses, among many others. One approach to conflation, attempted from the outset in the literature, is the use of optimization-based conflation methods.