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ORCIDPing Guo 0002
Person information
- affiliation: Beijing Normal University, Image Processing Pattern Recognition Laboratory, China
- affiliation (PhD 2002): Chinese University of Hong Kong, Hong Kong
Other persons with the same name
- Ping Guo — disambiguation page
- Ping Guo 0001 — University of Paderborn, Germany
- Ping Guo 0003
![[0000-0002-5239-8896]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-5239-8896")
— Chongqing University, College of Computer Science, China - Ping Guo 0004 — China Agricultural University, College of Water Conservancy and Civil Engineering, Beijing, China (and 1 more)
- Ping Guo 0005 — Dalian University of Technology, School of Mathematical Sciences, Liaoning, China
- Ping Guo 0006 — Shijiazhuang Tiedao University, School of Economics and Management, Shijiazhuang, Hebei, China
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2020 – today
- 2023
[j53]Xiaoxuan Sun, Xiaodan Deng, Qian Yin, Ping Guo:
An improved parameter learning methodology for RVFL based on pseudoinverse learners. Neural Comput. Appl. 35(2): 1803-1818 (2023)- 2022
- [j52]Hongbing Xia, Bo Zhao, Ping Guo:
Synergetic learning structure-based neuro-optimal fault tolerant control for unknown nonlinear systems. Neural Networks 155: 204-214 (2022) - [j51]Qian Yin, Bingxin Xu, Kaiyan Zhou, Ping Guo:
Bayesian Pseudoinverse Learners: From Uncertainty to Deterministic Learning. IEEE Trans. Cybern. 52(11): 12205-12216 (2022) - [j50]Haifeng Sima, Jing Wang, Ping Guo, Junding Sun, Hongmin Liu, Mingliang Xu, Youfeng Zou:
Composite Kernel of Mutual Learning on Mid-Level Features for Hyperspectral Image Classification. IEEE Trans. Cybern. 52(11): 12217-12230 (2022) - [c167]Liao Zhu, Jingsheng Xu, Ping Guo:
Data-Driven Suboptimal Control for Nonlinear Systems Using State-Dependent Riccati Equation. SMC 2022: 2845-2850 - 2021
- [j49]Ke Wang, Ping Guo:
A Robust Automated Machine Learning System with Pseudoinverse Learning. Cogn. Comput. 13(3): 724-735 (2021) - [j48]Shufeng Hao, Chongyang Shi, Longbing Cao, Zhendong Niu, Ping Guo:
Learning deep relevance couplings for ad-hoc document retrieval. Expert Syst. Appl. 183: 115335 (2021) - [j47]Xiaodan Deng, Mohammed A. B. Mahmoud, Qian Yin, Ping Guo:
An efficient and effective deep convolutional kernel pseudoinverse learner with multi-filter. Neurocomputing 457: 74-83 (2021) - [j46]Wenyi Zeng, Yue Xi, Qian Yin, Ping Guo:
Weighted dual hesitant fuzzy set and its application in group decision making. Neurocomputing 458: 714-726 (2021) - [j45]Yanan Liu, Yun Tian, Yang Xu, Shifeng Zhao, Yapei Huang, Yachun Fan, Fuqing Duan, Ping Guo:
TPGN: A Time-Preference Gate Network for e-commerce purchase intention recognition. Knowl. Based Syst. 220: 106920 (2021) - [j44]Mohammed A. B. Mahmoud, Ping Guo, Ahmed Fathy, Kan Li:
SRCNN-PIL: Side Road Convolution Neural Network Based on Pseudoinverse Learning Algorithm. Neural Process. Lett. 53(6): 4225-4237 (2021) - [j43]Mohammed A. B. Mahmoud, Ping Guo:
DNA sequence classification based on MLP with PILAE algorithm. Soft Comput. 25(5): 4003-4014 (2021) - [j42]Ke Wang, Ping Guo:
An Ensemble Classification Model With Unsupervised Representation Learning for Driving Stress Recognition Using Physiological Signals. IEEE Trans. Intell. Transp. Syst. 22(6): 3303-3315 (2021) - 2020
- [j41]Lei Qiao, Xuesong Li, Qasim Umer, Ping Guo:
Deep learning based software defect prediction. Neurocomputing 385: 100-110 (2020) - [j40]Hussain Dawood, Hassan Dawood, Ping Guo, Rashid Mehmood, Ali Daud, Abdullah Alamri, Jalal S. Alowibdi:
Probability weighted moments regularization based blind image De-blurring. Multim. Tools Appl. 79(7-8): 4483-4498 (2020) - [j39]Mohammed A. B. Mahmoud, Ping Guo, Ke Wang:
Pseudoinverse learning autoencoder with DCGAN for plant diseases classification. Multim. Tools Appl. 79(35-36): 26245-26263 (2020) - [c166]Bo Zhao, Jiaxu Hou, Ping Guo, Derong Liu, Yancai Xu:
Approximate Optimal Control of Nonlinear Systems with Mismatched Perturbations Based on Asymptotically Stable Critic Neural Network. ICCDE 2020: 60-64 - [c165]Xin Liu, Zenglin Xu, Ping Guo:
Causal Inference for Mixed-Type Data in Additive Noise Models. ICONIP (2) 2020: 223-234 - [c164]Xiaoxuan Sun, Rundong Shi, Bo Zhao, Ping Guo:
Boosting and Residual Learning Scheme with Pseudoinverse Learners. SMC 2020: 2136-2141 - [c163]Yanping Wang, Xin Xin, Ping Guo:
An Empirical Study of Pre-trained Embedding on Ultra-Fine Entity Typing. SMC 2020: 2656-2661 - [i6]Jiali Xu, Qian Yin, Ping Guo, Xin Zheng:
Two-dimensional Multi-fiber Spectrum Image Correction Based on Machine Learning Techniques. CoRR abs/2002.06600 (2020) - [i5]Ping Guo, Qian Yin:
Synergetic Learning Systems: Concept, Architecture, and Algorithms. CoRR abs/2006.06367 (2020)
2010 – 2019
- 2019
- [j38]Mohammed A. B. Mahmoud, Ping Guo:
A Novel Method for Traffic Sign Recognition Based on DCGAN and MLP With PILAE Algorithm. IEEE Access 7: 74602-74611 (2019) - [j37]Xiuling Zhou, Bingxin Xu, Ping Guo, Ning He:
Multi-channel expected patch log likelihood for color image denoising. Neurocomputing 367: 130-143 (2019) - [c162]Li-Jiao Wu, Zhi-Hui Zhan, Xiao-Min Hu, Ping Guo, Yanchun Zhang, Jun Zhang:
Multi-runway Aircraft Arrival Scheduling: A Receding Horizon Control Based Ant Colony System Approach. CEC 2019: 538-545 - [c161]Xiaoyu Dong, Xin Xin, Ping Guo:
Chinese NER by Span-Level Self-Attention. CIS 2019: 68-72 - [c160]Yan Wang, Xin Xin, Ping Guo:
Relation Extraction via Attention-Based CNNs using Token-Level Representations. CIS 2019: 113-117 - [c159]Wenyi Zeng, Guangchen Song, Qian Yin, Ping Guo:
Some new Distance Measures of Hesitant Fuzzy Sets and its Application in Group Decision Making. CIS 2019: 118-122 - [c158]Jiali Xu, Qian Yin, Ping Guo, Xin Zheng:
Effective Pulsar Dispersion Measure Estimation Based on Progressive Probabilistic Hough Transform. CIS 2019: 247-251 - [c157]Xiaodan Deng, Xiaoxuan Sun, Ping Guo, Qian Yin:
Image Recognition Based on Combined Filters with Pseudoinverse Learning Algorithm. AIAI 2019: 202-209 - [c156]Xinrui Jiang, Sitian Qin, Ping Guo:
A Gradient-Descent Neurodynamic Approach for Distributed Linear Programming. ISNN (2) 2019: 45-53 - [c155]Sibo Feng, Xiaodan Deng, Ping Guo, Bo Zhao, Qian Yin, Hongfeng Wang:
An Ensemble Model for Error Modeling with Pseudoinverse Learning Algorithm. SMC 2019: 1893-1898 - [c154]Ping Guo, Bo Zhao:
An Unified View on the Feedforward Neural Network Architecture. ICSI (2) 2019: 173-180 - 2018
- [j36]Ping Guo, Yuping Wang, Hai-Lin Liu, Yiu-ming Cheung:
Computational Intelligence in Astronomy: Preface. Int. J. Comput. Intell. Syst. 11(1): 573-574 (2018) - [j35]Ke Wang, Ping Guo, Fusheng Yu, Lingzi Duan, Yuping Wang, Hui Du:
Computational Intelligence in Astronomy: A Survey. Int. J. Comput. Intell. Syst. 11(1): 575-590 (2018) - [j34]Rubab Mehboob, Hassan Dawood, Hussain Dawood, Muhammad Usman Ilyas, Ping Guo, Ameen Banjar:
Live fingerprint detection using magnitude of perceived spatial stimuli and local phase information. J. Electronic Imaging 27(05): 053038 (2018) - [j33]Yongquan Yan, Ping Guo, Bin Cheng, Zhigao Zheng:
An experimental case study on the relationship between workload and resource consumption in a commercial web server. J. Comput. Sci. 25: 183-192 (2018) - [j32]Yanjun Li, Ping Guo:
Training neural networks by marginalizing out hidden layer noise. Neural Comput. Appl. 29(9): 401-412 (2018) - [j31]Haifeng Sima, Ping Guo, Youfeng Zou, Zhiheng Wang, Mingliang Xu:
Bottom-Up Merging Segmentation for Color Images With Complex Areas. IEEE Trans. Syst. Man Cybern. Syst. 48(3): 354-365 (2018) - [c153]Shijia Li, Sibo Feng, Ping Guo, Qian Yin:
A Hierarchical Model with Pseudoinverse Learning Algorithm Optimazation for Pulsar Candidate Selection. CEC 2018: 1-6 - [c152]Bingxin Xu, Ping Guo:
Pseudoinverse Learning Algorithom for Fast Sparse Autoencoder Training. CEC 2018: 1-6 - [c151]Asif Mehmood, Muhammad Javed Iqbal, Hassan Dawood, Ping Guo:
Computationally Efficient Low Power Neuron Model for Digital Brain. CIS 2018: 1-5 - [c150]Wenyi Zeng, Yue Xi, Qian Yin, Ping Guo:
Weighted Dual Hesitant Fuzzy Sets and Its Application in Group Decision Making. CIS 2018: 77-82 - [c149]Xiaoqiao Zhang, Xiuling Zhou, Ping Guo:
Hyperspectral Image Denoising Based on Low Rank and Expected Patch Log Likelihood. CIS 2018: 100-105 - [c148]Peng Wu, Qian Yin, Ping Guo:
A Two-Dimensional Sky Background Model for LAMOST Based on Improved KICA. CIS 2018: 476-480 - [c147]Zhen Wang, Qian Yin, Ping Guo, Xin Zheng:
Flux Extraction Based on General Regression Neural Network for Two-Dimensional Spectral Image. HCI (28) 2018: 219-226 - [c146]Xiaodan Deng, Sibo Feng, Ping Guo, Qian Yin:
Fast Image Recognition with Gabor Filter and Pseudoinverse Learning AutoEncoders. ICONIP (6) 2018: 501-511 - [c145]Yaran Chen, Dongbin Zhao, Haoran Li, Dong Li, Ping Guo:
A temporal-based deep learning method for multiple objects detection in autonomous driving. IJCNN 2018: 1-6 - [c144]Jue Wang, Ping Guo, Xin Xin:
Review of Pseudoinverse Learning Algorithm for Multilayer Neural Networks and Applications. ISNN 2018: 99-106 - [c143]Cuihua Ma, Ping Guo, Xin Xin:
Personalized Response Generation for Customer Service Agents. ISNN 2018: 476-483 - [c142]Bingxin Xu, Ping Guo:
Broad and Pseudoinverse Learning for Autoencoder. SMC 2018: 4243-4247 - [c141]Rui Wang, Ping Guo, Xin Fan, Biao Li, Wei Zhang, Xin Xin:
Listwise Click-Through Rate Prediction with Item-Item Interactions. SMC 2018: 4417-4423 - [c140]Deyi Wang, Jianchao Fan, Min Han, Ping Guo, Yuzhen Lu:
Marine Floating Raft Aquaculture Back Scattering Feature Analysis Based On ISAR Imagery. SSCI 2018: 1902-1905 - [c139]Jie Gao, Xin Xin, Junshuai Liu, Rui Wang, Jing Lu, Biao Li, Xin Fan, Ping Guo:
Fine-Grained Deep Knowledge-Aware Network for News Recommendation with Self-Attention. WI 2018: 81-88 - [i4]Li Si-Yao, Dongwei Ren, Zijian Hu, Junfeng Li, Qian Yin, Ping Guo:
A Concatenated Residual Network for Image Deblurring. CoRR abs/1804.06042 (2018) - [i3]Ping Guo, Xiuling Zhou, Ke Wang:
PILAE: A Non-gradient Descent Learning Scheme for Deep Feedforward Neural Networks. CoRR abs/1811.01545 (2018) - 2017
- [c138]Qiang Pan, Ping Guo, Xin Xin, Junshuai Liu:
Extracting Company-Specific Keyphrases from News Media. CIS 2017: 135-139 - [c137]Hang Yu, Zhen Wang, Qian Yin, Ping Guo:
A Comprehensive Study of Blind and Non-blind Deconvolution Methods Applied to Spectrum Extraction. CIS 2017: 484-487 - [c136]Muhammad Waqar, Hassan Dawood, Ping Guo, Muhammad Bilal Shahnawaz, Mustansar Ali Ghazanfar:
Prediction of Stock Market by Principal Component Analysis. CIS 2017: 599-602 - [c135]Rehan Mehmood Yousaf, Saad Rehman, Hassan Dawood, Ping Guo, Zahid Mehmood, Shoaib Azam, Abdullah Aman Khan:
Saliency Based Object Detection and Enhancements in Static Images. ICISA 2017: 114-123 - [c134]Xiuling Zhou, Jing Wang, Ping Guo, C. L. Philip Chen:
Mixture of Matrix Normal Distributions for Color Image Inpainting. ICONIP (3) 2017: 95-104 - [c133]Sibo Feng, Shijia Li, Ping Guo, Qian Yin:
Image Recognition with Histogram of Oriented Gradient Feature and Pseudoinverse Learning AutoEncoders. ICONIP (6) 2017: 740-749 - [c132]Hang Yu, Qian Yin, Ping Guo:
Pulsar Bayesian Model: A Comprehensive Astronomical Data Fitting Model. ICONIP (1) 2017: 904-911 - [c131]Hang Yu, Qian Yin, Ping Guo:
Enlightening the Relationship Between Distribution and Regression Fitting. IFIP TC12 ICIS 2017: 222-227 - [c130]Mingze Li, Hasitieer Haerken, Ping Guo, Fuqing Duan, Qian Yin, Xin Zheng:
Two-dimensional spectral image calibration based on feed-forward neural network. IJCNN 2017: 4194-4201 - [c129]Cuihua Ma, Ping Guo, Xin Xin, Xiaoyu Ma, Yanjie Liang, Shaomin Xing, Li Li, Shaozhuang Liu:
Collaborative Response Content Recommendation for Customer Service Agents. ISNN (1) 2017: 36-43 - [c128]Jian Hu, Xin Xin, Ping Guo:
LSTM with Matrix Factorization for Road Speed Prediction. ISNN (1) 2017: 242-249 - [c127]Kuai Zhang, Xin Xin, Pei Luo, Ping Guo:
Fine-grained news recommendation by fusing matrix factorization, topic analysis and knowledge graph representation. SMC 2017: 918-923 - [c126]Pei Luo, Xin Xin, Kuai Zhang, Ping Guo, Yang Yu, Zichao Wang:
Predicting the number of driving service orders in fine-grained regions by an ensemble multi-view-based model. SMC 2017: 936-941 - [c125]Ke Wang, Ping Guo, Xin Xin, Zebin Ye:
Autoencoder, low rank approximation and pseudoinverse learning algorithm. SMC 2017: 948-953 - [i2]Li Si-Yao, Qian Yin, Ping Guo:
Understanding and Eliminating the Large-kernel Effect in Blind Deconvolution. CoRR abs/1706.01797 (2017) - [i1]Ping Guo, Fuqing Duan, Pei Wang, Yao Yao, Xin Xin:
Pulsar Candidate Identification with Artificial Intelligence Techniques. CoRR abs/1711.10339 (2017) - 2016
- [j30]Yongquan Yan, Ping Guo:
Predicting Software Abnormal State by using Classification Algorithm. J. Database Manag. 27(2): 49-65 (2016) - [j29]Sulan Zhang, Jifu Zhang, Ping Guo, Meng Chu, Kai-Hsiung Chang:
A FWCL-based method for visual vocabulary formation. Multim. Tools Appl. 75(1): 647-665 (2016) - [j28]Yuanlong Wang, Ping Guo, Fuqing Duan:
A fast ray tracing algorithm based on a hybrid structure. Multim. Tools Appl. 75(4): 1883-1898 (2016) - [c124]Hasitieer Haerken, Fuqing Duan, Jiannan Zhang, Ping Guo:
An Effective Method for Modeling Two-dimensional Sky Background of LAMOST. Astroinformatics 2016: 63-66 - [c123]Yao Yao, Xin Xin, Ping Guo:
Pulsar Candidate Selection by Assembling Positive Sample Emphasized Classifiers. CIS 2016: 120-124 - [c122]Jianjun Xie, Junhong Li, Hong Wang, Wenyi Zeng, Ping Guo:
The Methods for Two-Dimensional Fiber Spectra Extraction. CIS 2016: 487-490 - [c121]Yanjun Li, Ping Guo, Xin Xin:
A Divide and Conquer Method for Automatic Image Annotation. CIS 2016: 660-664 - [c120]Liang Wang, Chao Shen, Fuqing Duan, Ping Guo:
Energy-Based Multi-plane Detection from 3D Point Clouds. ICONIP (2) 2016: 715-722 - [c119]Yao Yao, Xin Xin, Ping Guo:
A rank minimization-based late fusion method for multi-label image annotation. ICPR 2016: 847-852 - [c118]Ke Wang, Ping Guo, Qian Yin, A-Li Luo, Xin Xin:
A pseudoinverse incremental algorithm for fast training deep neural networks with application to spectra pattern recognition. IJCNN 2016: 3453-3460 - [c117]Peng Wu, Qian Yin, Ping Guo:
Kernel selection with evolutionary algorithm for multiple kernel independent component analysis. IJCNN 2016: 4147-4153 - [c116]Min Yan, Qian Yin, Ping Guo:
Image stitching with single-hidden layer feedforward neural networks. IJCNN 2016: 4162-4169 - [c115]Bingxin Xu, Qian Yin, Ping Guo, Hongzhe Liu:
Image representation via sub-dictionary based sparse coding. IJCNN 2016: 5113-5118 - [c114]Ping Guo, Jian Yu, Qian Yin:
Long Exposure Point Spread Function Modeling with Gaussian Processes. ISNN 2016: 540-546 - [c113]Peng Ji, Xin Xin, Ping Guo:
Fine-Grained Real Estate Estimation Based on Mixture Models. ISNN 2016: 555-564 - [c112]Ke Wang, Ping Guo, A-Li Luo, Xin Xin, Fuqing Duan:
Deep neural networks with local connectivity and its application to astronomical spectral data. SMC 2016: 2687-2692 - 2015
- [j27]Yao Yao, Ping Guo, Xin Xin, Ziheng Jiang:
Erratum to: Image Fusion by Hierarchical Joint Sparse Representation. Cogn. Comput. 7(5): 633 (2015) - [j26]Peng Wu, Fuqing Duan, Ping Guo:
A pre-selecting base kernel method in multiple kernel learning. Neurocomputing 165: 46-53 (2015) - [j25]Hassan Dawood, Hussain Dawood, Ping Guo:
Removal of random-valued impulse noise by local statistics. Multim. Tools Appl. 74(24): 11485-11498 (2015) - [c111]Ke Wang, Ping Guo, A-Li Luo:
Angular quantization based affinity propagation clustering and its application to astronomical big spectra data. IEEE BigData 2015: 601-608 - [c110]Hassan Dawood, Hussain Dawood, Ping Guo:
A Hybrid Image Feature Descriptor for Classification. CIS 2015: 58-61 - [c109]Yiren Wang, Hassan Dawood, Qian Yin, Ping Guo:
A comparative study of different feature mapping methods for image annotation. ICACI 2015: 340-344 - [c108]Shiqiang Li, Hussain Dawood, Ping Guo:
Comparison of linear dimensionality reduction methods in image annotation. ICACI 2015: 355-360 - [c107]Yanjun Li, Xin Xin, Ping Guo:
Neural Networks with Marginalized Corrupted Hidden Layer. ICONIP (3) 2015: 506-514 - [c106]Xin Xin, Zhirun Liu, Chin-Yew Lin, Heyan Huang, Xiaochi Wei, Ping Guo:
Cross-Domain Collaborative Filtering with Review Text. IJCAI 2015: 1827-1834 - 2014
- [j24]Yao Yao, Ping Guo, Xin Xin, Ziheng Jiang:
Image Fusion by Hierarchical Joint Sparse Representation. Cogn. Comput. 6(3): 281-292 (2014) - [j23]Bingxin Xu, Ping Guo, C. L. Philip Chen:
An adaptive regularization method for sparse representation. Integr. Comput. Aided Eng. 21(1): 91-100 (2014) - [j22]Qian Yin, Ruiyi Luo, Ping Guo:
Software Fault Estimation Framework based on aiNet. Int. J. Comput. Intell. Syst. 7(4): 715-723 (2014) - [j21]Haifeng Sima, Ping Guo:
Texture Superpixels Merging by Color-texture Histograms for Color Image Segmentation. KSII Trans. Internet Inf. Syst. 8(7): 2400-2419 (2014) - [j20]Minguang Song, Ping Guo:
Combining Local Binary Patterns for Scene Recognition. J. Softw. 9(1): 203-210 (2014) - [j19]Xiao Zhi Gao, Jing Wang, Jarno M. A. Tanskanen, Rongfang Bie, Xiaolei Wang, Ping Guo, Kai Zenger:
Optimal Classification of Epileptic EEG Signals Using Neural Networks and Harmony Search Methods. J. Softw. 9(1): 230-239 (2014) - [j18]Hussain Dawood, Hassan Dawood, Ping Guo:
Removal of high-intensity impulse noise by Weber's law Noise Identifier. Pattern Recognit. Lett. 49: 121-130 (2014) - [c105]Deqing Li, Wenyi Zeng, Junhong Li, Ping Guo:
Balance Function Analysis in Variable Weight Decision Making. CIS 2014: 30-34 - [c104]Bu Chen, Qian Yin, Ping Guo:
A Study of Deep Belief Network Based Chinese Speech Emotion Recognition. CIS 2014: 180-184 - [c103]Xin Zheng, Chenlei Lv, Qingqing Xu, Ping Guo:
Image Up-Scaling: Based on Self Similarity and Local Information. CIS 2014: 233-237 - [c102]Hassan Dawood, Hussain Dawood, Ping Guo:
Texture Image Classification with Improved Weber Local Descriptor. ICAISC (1) 2014: 684-692 - [c101]Peng Wu, Qian Yin, Ping Guo:
Method of Evolving Non-stationary Multiple Kernel Learning. ICONIP (2) 2014: 17-25 - [c100]Yanjun Li, Ping Guo, Xin Xin:
An Improved Separating Hyperplane Method with Application to Embedded Intelligent Devices. ICONIP (2) 2014: 118-125 - [c99]Song Lin, Ping Guo, Xin Xin:
Supervised topic regression via experts. IJCNN 2014: 3526-3533 - [c98]Jian Yu, Ping Guo, A-Li Luo:
Adaptive regularization deconvolution extraction algorithm for spectral signal processing. INISTA 2014: 375-380 - [c97]Yongquan Yan, Ping Guo, Lifeng Liu:
A Novel Hybridization of Artificial Neural Networks and ARIMA Models for Forecasting Resource Consumption in an IIS Web Server. ISSRE Workshops 2014: 437-442 - [c96]Yongquan Yan, Ping Guo, Lifeng Liu:
A Practice of Forecasting Software Aging in an IIS Web Server Using SVM. ISSRE Workshops 2014: 443-448 - [c95]Junhong Li, Wenyi Zeng, Ping Guo:
Interval-valued intuitionistic trapezoidal fuzzy number and its application. SMC 2014: 734-737 - [c94]Ke Wang, Ping Guo:
An efficient and scalable learning algorithm for Near-Earth objects detection in astronomy big image data. SMC 2014: 742-747 - 2013
- [j17]Jing Wang, Xiao Zhi Gao, Ping Guo:
Feature extraction based on sparse representation with application to epileptic EEG classification. Int. J. Imaging Syst. Technol. 23(2): 104-113 (2013) - [j16]Bingxin Xu, Rukun Hu, Ping Guo:
Combining affinity propagation with supervised dictionary learning for image classification. Neural Comput. Appl. 22(7-8): 1301-1308 (2013) - [j15]Xiuling Zhou, Ping Guo, C. L. Philip Chen:
Covariance Matrix Estimation with Multi-Regularization Parameters based on MDL Principle. Neural Process. Lett. 38(2): 227-238 (2013) - [c93]