Q
Qiang He
Researcher at Swinburne University of Technology
Publications - 547
Citations - 13588
Qiang He is an academic researcher from Swinburne University of Technology. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 50, co-authored 389 publications receiving 8498 citations. Previous affiliations of Qiang He include Huazhong University of Science and Technology & Shanghai Jiao Tong University.
Papers
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Journal ArticleDOI
A novel framework of fuzzy oblique decision tree construction for pattern classification
TL;DR: The experimental results demonstrate that the fuzzy oblique decision tree (FODT) exhibits better performance on classification accuracy and tree size than the chosen benchmarks.
Journal ArticleDOI
Fat-water separation based on Transition REgion Extraction (TREE).
Hao Peng,Hao Peng,Chao Zou,Cheng Chuanli,Tie Changjun,Qiao Yangzi,Qian Wan,Jianxun Lv,Qiang He,Dong Liang,Xin Liu,Wenzhong Liu,Hairong Zheng +12 more
TL;DR: To develop a method based on fat‐water transition region extraction (TREE) for robustfat‐water separation and quantification in challenging scenarios, including low signal‐to‐noise ratio (SNR), fast changing B0 field, and disjointed anatomies.
Proceedings ArticleDOI
DeepWSC: A Novel Framework with Deep Neural Network for Web Service Clustering
TL;DR: A novel framework with deep neural network, called DeepWSC, is proposed, which combines the advantages of recurrent neural network and convolutional neural network to cluster web services through automatic feature extraction.
Book ChapterDOI
Indicator-Based Multi-objective Bacterial Foraging Algorithm with Adaptive Searching Mechanism
TL;DR: The main idea of I-MOBCA is to develop an adaptive and cooperative model by combining bacterial foraging, adaptive searching, cell-to-cell communication and preference indicator-based measure strategies, which can essentially reduce the computation complexity.
Journal ArticleDOI
PLOFR: An Online Flow Route Framework for Power Saving and Load Balance in SDN
TL;DR: This article proposes a Power-efficient and Load-balanced Online Flow Route framework, and proposes a route updating algorithm to enable path updating caused by flow scheduling and demonstrates the proposed algorithm outperforms benchmarks on power saving, load balance, and reduces the possibility of link congestion.