Le Zhang - Google Scholar Citations

Cited by

	All	Since 2015
Citations	1654	1650
h-index	18	18
i10-index	25	25

820

410

205

615

20152016201720182019202016 95 230 431 807 66

Co-authors

Dr P. N. SuganthanEEE, NTUVerified email at ntu.edu.sg
Ming-Ming Cheng, 程明明Professor, CS, Nankai UniversityVerified email at nankai.edu.cn
Yun LiuNankai UniversityVerified email at mail.nankai.edu.cn
Jia-Wang Bian, 边佳旺University of AdelaideVerified email at adelaide.edu.au
ZHENGHUA CHENInstitute for Infocomm Research (I2R), A*STAR, SingaporeVerified email at ntu.edu.sg
Zenglin ShiUniversity of AmsterdamVerified email at uva.nl
Zhiguang CaoNational University of SingaporeVerified email at nus.edu.sg
Gehan AmaratungaProfessor of Electrical Engineering, University of CambridgeVerified email at cam.ac.uk
Jagannadan VaradarajanHead of Data Science (Machine Learning & Maps), GrabVerified email at grab.com
Pierre MoulinProfessor, University of Illinois at Urbana-ChampaignVerified email at ifp.uiuc.edu
Guoyan Zheng, Prof. Dr.Professor of Shanghai Jiao Tong University, ChinaVerified email at ieee.org
Wei CuiNangyang Technological UniversityVerified email at e.ntu.edu.sg
Lihua XieProfessor of Electrical Engineering, Nanyang Technological UniversityVerified email at ntu.edu.sg
Deng-Ping FanInception Institute of Artificial Intelligence (IIAI); Nankai UniversityVerified email at inceptioniai.org
Qingchang ZhuTencent, Ph. D from Nanyang Technological UniversityVerified email at e.ntu.edu.sg
Stefan WinklerIEEE Fellow, Deputy Director @AI Singapore, Associate Professor @NUSVerified email at nus.edu.sg
Songyou PengETH Zurich and Max Planck Institute for Intelligent SystemsVerified email at inf.ethz.ch
Wei MengTemasek Laboratories, National University of SingaporeVerified email at nus.edu.sg
Bing LiThe University of New South WalesVerified email at unsw.edu.au
Narendra AhujaDonald Biggar Willet Professor, University of Illinois at Urbana-ChampagnVerified email at illinois.edu

Le Zhang

Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR)

Verified email at e.ntu.edu.sg - Homepage

machine learning computer vision


Title	Cited by	Year
Ensemble classification and regression-recent developments, applications and future directions Y Ren, L Zhang, PN Suganthan IEEE Computational intelligence magazine 11 (1), 41-53, 2016	222	2016
Richer Convolutional Features for Edge Detection Y Liu, MM Cheng, X Hu, JW Bian, L Zhang, X Bai, J Tang IEEE Transactions on Pattern Analysis and Machine Intelligence 41 (8), 1939 …, 2019	217	2019
A survey of randomized algorithms for training neural networks L Zhang, PN Suganthan Information Sciences 364, 146-155, 2016	170	2016
Ensemble deep learning for regression and time series forecasting X Qiu, L Zhang, Y Ren, PN Suganthan, G Amaratunga 2014 IEEE symposium on computational intelligence in ensemble learning (CIEL …, 2014	163	2014
A comprehensive evaluation of random vector functional link networks L Zhang, PN Suganthan Information sciences 367, 1094-1105, 2016	146	2016
Random forests with ensemble of feature spaces L Zhang, PN Suganthan Pattern Recognition 47 (10), 3429-3437, 2014	87	2014
Crowd counting with deep negative correlation learning Z Shi, L Zhang, Y Liu, X Cao, Y Ye, MM Cheng, G Zheng Proceedings of the IEEE conference on computer vision and pattern …, 2018	74	2018
Robust human activity recognition using smartphone sensors via CT-PCA and online SVM Z Chen, Q Zhu, YC Soh, L Zhang IEEE Transactions on Industrial Informatics 13 (6), 3070-3080, 2017	67	2017
Oblique Decision Tree Ensemble via Multisurface Proximal Support Vector Machine L Zhang, PN Suganthan Cybernetics, IEEE Transactions on 45 (10), 2165 - 2176, 2014	63	2014
Robust visual tracking using oblique random forests L Zhang, J Varadarajan, P Nagaratnam Suganthan, N Ahuja, P Moulin Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017	52	2017
Visual tracking with convolutional random vector functional link network L Zhang, PN Suganthan IEEE transactions on cybernetics 47 (10), 3243-3253, 2016	46	2016
Robust visual tracking via co-trained kernelized correlation filters L Zhang, PN Suganthan Pattern Recognition 69, 82-93, 2017	39	2017
Benchmarking ensemble classifiers with novel co-trained kernel ridge regression and random vector functional link ensembles [research frontier] L Zhang, PN Suganthan IEEE Computational Intelligence Magazine 12 (4), 61-72, 2017	38	2017
Contrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection JX Zhao, Y Cao, DP Fan, MM Cheng, XY Li, L Zhang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019	23	2019
Received signal strength based indoor positioning using a random vector functional link network W Cui, L Zhang, B Li, J Guo, W Meng, H Wang, L Xie IEEE Transactions on Industrial Informatics 14 (5), 1846-1855, 2017	22	2017
Towards generating random forests via extremely randomized trees L Zhang, Y Ren, PN Suganthan 2014 International Joint Conference on Neural Networks (IJCNN), 2645-2652, 2014	20	2014
Distilling the knowledge from handcrafted features for human activity recognition Z Chen, L Zhang, Z Cao, J Guo IEEE Transactions on Industrial Informatics 14 (10), 4334-4342, 2018	19	2018
An ensemble of decision trees with random vector functional link networks for multi-class classification R Katuwal, PN Suganthan, L Zhang Applied Soft Computing 70, 1146-1153, 2018	18	2018
Kernel cross-correlator C Wang, L Zhang, L Xie, J Yuan Thirty-Second AAAI Conference on Artificial Intelligence, 2018	17	2018
Oblique random forest ensemble via Least Square Estimation for time series forecasting X Qiu, L Zhang, PN Suganthan, GAJ Amaratunga Information Sciences 420, 249-262, 2017	17	2017

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