J
Jie Yang
Researcher at Shanghai Jiao Tong University
Publications - 680
Citations - 12772
Jie Yang is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Image segmentation & Feature extraction. The author has an hindex of 46, co-authored 629 publications receiving 10558 citations. Previous affiliations of Jie Yang include East China University of Science and Technology & Chinese Ministry of Education.
Papers
More filters
Journal ArticleDOI
Multi-task classification with sequential instances and tasks
TL;DR: The method attempts to jointly learn the task curriculum and the instance curriculum by introducing a self-paced item for the instances of each task in the existing multi-task learning framework Sequential Multi-Task learning (SeqMT), which transfers information from the previously learned tasks to the next ones through shared task parameters.
Journal ArticleDOI
Efficient cellular automaton segmentation supervised by pyramid on medical volumetric data and real time implementation with graphics processing unit
TL;DR: A user interactive segmentation method: given a labeled 2D image plane in Multi-Planar Reformation (MPR), the rest tissues are segmented automatically by a cellular automaton in multi-scale domain and shows the merits of higher precision, real time response in GPU framework and few interactions.
Journal ArticleDOI
Desulfurization of Simulated Oils by Microwave Chemical Methods
TL;DR: In this paper, the desulfurization efficiencies of BBPV, formylhydroperoxide and peroxyacetic acid for an oil sample (simulated oil 2) containing bi-benzothiophene were better than for the oil sample containing benzothiopane.
Journal ArticleDOI
Point target detection of infrared images with eigentargets
TL;DR: A novel detection method for infrared (IR) point targets based on eigentargets, which has better performance with better receiver operating characteristics, and larger signal-to-noise ratio (SNR) and background suppression factor.
Journal ArticleDOI
Alleviating Class-Wise Gradient Imbalance for Pulmonary Airway Segmentation
TL;DR: In this article, a General Union loss function was proposed to avoid the impact of airway size by distance-based weights and adaptively tune the gradient ratio based on the learning process.