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zhiquan qi, 齐志泉
zhiquan qi, 齐志泉
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Titel
Zitiert von
Zitiert von
Jahr
Automatic Road Crack Detection Using Random Structured Forests
zhiquan qi
1016*
Robust twin support vector machine for pattern classification
Z Qi, Y Tian, Y Shi
Pattern recognition 46 (1), 305-316, 2013
3452013
Nonparallel support vector machines for pattern classification
Y Tian, Z Qi, X Ju, Y Shi, X Liu
IEEE transactions on cybernetics 44 (7), 1067-1079, 2013
2552013
Laplacian twin support vector machine for semi-supervised classification
Z Qi, Y Tian, Y Shi
Neural networks 35, 46-53, 2012
2102012
Structural twin support vector machine for classification
Z Qi, Y Tian, Y Shi
Knowledge-based systems 43, 74-81, 2013
1542013
Twin support vector machine with universum data
Z Qi, Y Tian, Y Shi
Neural Networks 36, 112-119, 2012
1392012
Learning to incorporate structure knowledge for image inpainting
J Yang, Z Qi, Y Shi
Proceedings of the AAAI conference on artificial intelligence 34 (07), 12605 …, 2020
1232020
Support vector machine classifier with truncated pinball loss
X Shen, L Niu, Z Qi, Y Tian
Pattern Recognition 68, 199-210, 2017
1022017
Unsupervised anomaly segmentation via deep feature reconstruction
Y Shi, J Yang, Z Qi
Neurocomputing 424, 9-22, 2021
952021
When ensemble learning meets deep learning: a new deep support vector machine for classification
Z Qi, B Wang, Y Tian, P Zhang
Knowledge-Based Systems 107, 54-60, 2016
802016
Online multiple instance boosting for object detection
Z Qi, Y Xu, L Wang, Y Song
Neurocomputing 74 (10), 1769-1775, 2011
752011
Support vector regression for newspaper/magazine sales forecasting
X Yu, Z Qi, Y Zhao
Procedia Computer Science 17, 1055-1062, 2013
742013
Improved twin support vector machine
Y Tian, X Ju, Z Qi, Y Shi
Science China Mathematics 57, 417-432, 2014
682014
Pavement distress detection using random decision forests
L Cui, Z Qi, Z Chen, F Meng, Y Shi
Data Science: Second International Conference, ICDS 2015, Sydney, Australia …, 2015
612015
Efficient railway tracks detection and turnouts recognition method using HOG features
Z Qi, Y Tian, Y Shi
Neural Computing and Applications 23, 245-254, 2013
612013
A novel clustering-based image segmentation via density peaks algorithm with mid-level feature
Y Shi, Z Chen, Z Qi, F Meng, L Cui
Neural Computing and Applications 28, 29-39, 2017
582017
Dfr: Deep feature reconstruction for unsupervised anomaly segmentation
J Yang, Y Shi, Z Qi
arXiv preprint arXiv:2012.07122, 2020
522020
A survey on semantic segmentation
B Li, Y Shi, Z Qi, Z Chen
2018 IEEE International Conference on Data Mining Workshops (ICDMW), 1233-1240, 2018
492018
Image segmentation via improving clustering algorithms with density and distance
Z Chen, Z Qi, F Meng, L Cui, Y Shi
Procedia Computer Science 55, 1015-1022, 2015
462015
支持向量机中的核参数选择问题
齐志泉, 田英杰, 徐志洁
控制工程 12 (4), 379-381, 2005
46*2005
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