Qingyao Wu
Qingyao Wu
School of Software Engineering, South China University of Technology
Verified email at scut.edu.cn - Homepage
Cited by
Cited by
Discrimination-aware channel pruning for deep neural networks
Z Zhuang, M Tan, B Zhuang, J Liu, Y Guo, Q Wu, J Huang, J Zhu
arXiv preprint arXiv:1810.11809, 2018
Microalgae mass production methods
Y Shen, W Yuan, ZJ Pei, Q Wu, E Mao
Transactions of the ASABE 52 (4), 1275-1287, 2009
Stratified sampling for feature subspace selection in random forests for high dimensional data
Y Ye, Q Wu, JZ Huang, MK Ng, X Li
Pattern Recognition 46 (3), 769-787, 2013
ForesTexter: An efficient random forest algorithm for imbalanced text categorization
Q Wu, Y Ye, H Zhang, MK Ng, SS Ho
Knowledge-Based Systems 67, 105-116, 2014
A unified framework for metric transfer learning
Y Xu, SJ Pan, H Xiong, Q Wu, R Luo, H Min, H Song
IEEE Transactions on Knowledge and Data Engineering 29 (6), 1158-1171, 2017
Visual grounding via accumulated attention
C Deng, Q Wu, Q Wu, F Hu, F Lyu, M Tan
Proceedings of the IEEE conference on computer vision and pattern …, 2018
Pyramid graph networks with connection attentions for region-based one-shot semantic segmentation
C Zhang, G Lin, F Liu, J Guo, Q Wu, R Yao
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests
TT Nguyen, JZ Huang, Q Wu, TT Nguyen, MJ Li
BMC genomics 16 (2), 1-11, 2015
MR-NTD: Manifold regularization nonnegative tucker decomposition for tensor data dimension reduction and representation
X Li, MK Ng, G Cong, Y Ye, Q Wu
IEEE transactions on neural networks and learning systems 28 (8), 1787-1800, 2016
ML-FOREST: A multi-label tree ensemble method for multi-label classification
Q Wu, M Tan, H Song, J Chen, MK Ng
IEEE transactions on knowledge and data engineering 28 (10), 2665-2680, 2016
Online transfer learning with multiple homogeneous or heterogeneous sources
Q Wu, H Wu, X Zhou, M Tan, Y Xu, Y Yan, T Hao
IEEE Transactions on Knowledge and Data Engineering 29 (7), 1494-1507, 2017
Attention guided network for retinal image segmentation
S Zhang, H Fu, Y Yan, Y Zhang, Q Wu, M Yang, M Tan, Y Xu
International Conference on Medical Image Computing and Computer-Assisted …, 2019
Semi-Supervised Optimal Transport for Heterogeneous Domain Adaptation.
Y Yan, W Li, H Wu, H Min, M Tan, Q Wu
IJCAI 7, 2969-2975, 2018
SNP selection and classification of genome-wide SNP data using stratified sampling random forests
Q Wu, Y Ye, Y Liu, MK Ng
IEEE transactions on nanobioscience 11 (3), 216-227, 2012
Collaborative unsupervised domain adaptation for medical image diagnosis
Y Zhang, Y Wei, Q Wu, P Zhao, S Niu, J Huang, M Tan
IEEE Transactions on Image Processing 29, 7834-7844, 2020
Learning Discriminative Correlation Subspace for Heterogeneous Domain Adaptation.
Y Yan, W Li, MKP Ng, M Tan, H Wu, H Min, Q Wu
IJCAI, 3252-3258, 2017
Auto-embedding generative adversarial networks for high resolution image synthesis
Y Guo, Q Chen, J Chen, Q Wu, Q Shi, M Tan
IEEE Transactions on Multimedia 21 (11), 2726-2737, 2019
Breaking winner-takes-all: Iterative-winners-out networks for weakly supervised temporal action localization
R Zeng, C Gan, P Chen, W Huang, Q Wu, M Tan
IEEE Transactions on Image Processing 28 (12), 5797-5808, 2019
From whole slide imaging to microscopy: Deep microscopy adaptation network for histopathology cancer image classification
Y Zhang, H Chen, Y Wei, P Zhao, J Cao, X Fan, X Lou, H Liu, J Hou, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2019
Adversarial learning with local coordinate coding
J Cao, Y Guo, Q Wu, C Shen, J Huang, M Tan
International Conference on Machine Learning, 707-715, 2018
The system can't perform the operation now. Try again later.
Articles 1–20