[name]

[Our mission] We aim at proposing efficient, effective and intelligent models, algorithms and systems with application to machine vision and olfaction. Currently, we particularly focus on statistical machine learning models (transfer learning, discriminative learning, representational learning, subspace learning, manifold learning, metric learning, multi-view learning, sparse coding) and deep learning algorithms (transfer learning, adversarial learning, convolutional neural networks, generative learning, extreme learning machine, unsupervised domain adaptation) for large-scale visual/image classification, face analysis, fine-grained image recognition, and object/pedestrian recognition/detection (computer vision tasks), electronic nose and electronic tongue (machine olfaction tasks for odor, smell and taste analysis), and try to make our tiny endeavor for artificial intelligence (the 4th Technological Revolution). We always welcome any collaborations and highly motivated students (B.Sc, Master, Ph.D, Postdoc) join us in research and development.

[note]: Our group is looking for 8 students per year (for Master or Ph.D degree) with a strong interest in research. There are also 2 PostDoc positions available per year. Motivated Undergraduate students are also welcome. If you are interested in working with us, please contact me by email to leizhang@cqu.edu.cn. Please attach your CV in contacting.

Research Interests

Machine Intelligence, Computer Vision, Machine Olfaction, Machine Learning/Pattern Recognition, Signal/Image Processing

Key Research Direction

Machine Learning (human brain):

Deep learning, transfer learning, hashing learning, adversarial learning, multi-view/modal learning, subspace learning, discriminative/generative learning, metric learning, extreme learning

Machine Vision (human eye):

Computer vision-object recognition/image classification/face recognition, object/pedestrian detection/search, person re-identification, image/face synthesis, intelligent video surveillance, classification/recognition/regression, pattern recognition

Machine Olfaction (human nose):

Multi-sensor system, information fusion, electronic noses/tongue, sensor arrays, odor recognition

[LiVE Group News]

[ESI Highly cited paper] One paper "Lei Zhang and David Zhang, Domain Adaptation Extreme Learning Machines for Drift Compensation in E-Nose Systems, IEEE Transactions on Instrumentation and Measurement, vol. 64, no. 7, pp. 1790-1801, 2015" is selected as Highly cited paper by ESI.

[30/10/2017] Our paper “Adv-Kin: An Adversarial Convolutional Network for Kinship Verification” is granted as the "Best Paper Award" by the 12th Chinese Conference on Biometric Recognition (CCBR).

[11/10/2017] I am elected as the Computer Vision Committee of China Computer Federation (CCF).

[15/09/2017] I am elected as the Smart Services Professional Committee of Chinese Association for Artificial Intelligence (CAAI).

[Editoral] Lei Zhang, Sunil Kr. Jha, Zhixin Yang, Zhenbing Zhao, and Bhupendra Nath Tiwari, "Machine Intelligence in Signal Sensing, Processing, and Recognition," Journal of Electrical and Computer Engineering, vol. 2017, pp. 1-2, 2017.

[23/08/2017] 1 paper "Class-specific Reconstruction Transfer Learning via Sparse Low-rank Constraint" is accepted as Oral paper in IEEE Int'Conf. Computer Vision (ICCV), Workshop on CEFRL: Compact and Efficient Feature Representation and Learning in Computer Vision. Venice, Italy, Oct 2017.

[22/08/2017] 1 paper "From Face Recognition to Kinship Verification: An Adaptation Approach" is accepted as a Full paper in IEEE Int'Conf. Computer Vision (ICCV), Workshop on Analysis and Modeling of Faces and Gestures (AMFG). Venice, Italy, Oct 2017. [paper and source code coming soon]

[19/08/2017] 1 paper "AdvNet: Adversarial Contrastive Residual Net for 1 Million Kinship Recognition" is accepted as a Full paper in ACM Conf. Multimedia (ACM MM), 2017. Oral presentation. This paper is for RFIW Challenge in California, USA. [paper and source code coming soon]

[17/08/2017] 1 project is supported by National Natural Science Foundation of China (NSFC), $660K, 01/2018~12/2021.

[15/08/2017] 1 paper "Adv-Kin: An Adversarial Convolutional Network for Kinship Verification" is accepted in CCBR, 2017. [paper and source code coming soon]

[05/08/2017] 1 paper "Domain Class Consistency based Transfer Learning for Image Classification Across Domains" is accepted in Information Sciences, 2017.

[28/07/2017] 1 paper "Hierarchical Pruning Discriminative Extreme Learning Machine" is accepted in ELM, 2017.

[17/07/2017] 1 paper "Sparse Softmax Vector Coding based Deep Cascade Model" is accepted in CCCV, 2017. Acceptance rate: 42% (196/464). [paper and source code coming soon]

[24/06/2017] 1 paper "Anti-Drift in E-nose: A Subspace Projection Approach with Drift Reduction" is accepted in Sensors and Actuators B: Chemical, 2017.

[19/06/2017] 1 paper "Block-diagonal constrained Low-rank and Sparse Graph for Discriminant Analysis of Image Data" is accepted in Sensors, 2017.

[15/06/2017] 1 paper "DANoC: An Efficient Algorithm and Hardware Co-design of Deep Neural Networks on Chip" is accepted in IEEE Transactions on Neural Networks and Learning Systems, 2017.

[25/04/2017] 2 papers are accepted in Cognitive Computation, 2017.

[ICONIP2017 Call for Papers] I have organized an Invited Session (Chair: Lei Zhang and Shenglan Liu) on "Transfer Learning for Large-scale Domain Data (NIPS-04)" in ICONIP2017 (Neural Information Processing), Nov 14-18, Guangzhou, China. Welcome to submit your new research papers. Submission Deadline: June 15, 2017; Notice of Acceptance: Jul 31, 2017.

[08/04/2017] One paper "Lei Zhang, David Zhang, Ming-Ming Sun, and Fang-Mei Chen, Facial Beauty Analysis based on Geometric Feature: Toward Attractiveness Assessment Applications," is accepted in Expert Systems with Applications, [link], 2017.

[06/04/2017] I will give an invited talk on "Transfer learning in data mining" in FSDM2017, Taiwan.

[31/03/2017] One paper "Lei Zhang and Pingling Deng, Abnormal Odor Detection in Electronic Nose via Self-expression Inspired Learning Machine," is accepted in IEEE Transactions on Systems, Man, and Cybernetics: Systems, [link], 2017.

[24/03/2017] One paper "A Spatial-Temporal Method to Detect Global Influenza Epidemics Using Heterogeneous Data Collected from the Internet" is accepted in IEEE Transactions on Computational Biology and Bioinformatics, 2017.

[07/02/2017] One paper "Lei Zhang, Zhenwei He, and Yan Liu, Deep Object Recognition Across Domains based on Adaptive Extreme Learning Machine," is accepted in Neurocomputing, [link], 2017.

[04/12/2016] One paper "Lei Zhang, Yan Liu, and Pingling Deng, Odor Recognition in Multiple E-nose Systems with Cross-domain Discriminative Subspace Learning," is accepted as regular paper in IEEE Transactions on Instrumentation and Measurement, 2017. [paper and code are available]

[ESI Hot paper & Highly cited paper] One paper "L. Zhang, W. Zuo, and D. Zhang, LSDT: Latent Sparse Domain Transfer Learning for Visual Adaptation, IEEE Transactions on Image Processing, vol. 25, no. 3, pp. 1177-1191, 2016" is selected as Hot paper and Highly cited paper in 2016.8 by ESI. [link]

[SCI Journal Call for papers] I have been invited as the Lead Guest Editor of Journal of Electrical and Computer Engineering (SCI index), and organized a Special Issue on "Machine Intelligence in Signal Sensing, Processing and Recognition (MISS)". Welcome to submit your new research papers. Submission Deadline: April 11, 2017; First Decision: June 02, 2017; Publication: July 28, 2017.[CFP]

[02/11/2016] One paper "Tao Liu, Lei Zhang, Yanbing Chen, Dongqi Li and Xingrui Cui, Electronic Nose Based Beverage Identification by an Improved Fisher Discriminate Analysis Method," is accepted in IEEE AMC, 2016.

[22/10/2016] One paper "Lei Zhang and David Zhang, Cost-sensitive Discriminative Learning with Application to Vision and Olfaction," is accepted as regular paper in IEEE Transactions on Instrumentation and Measurement, 2016. [paper], [code is coming soon]

[28/09/2016] One paper "Pingling Deng and Lei Zhang , Olfactory Target/Background Odor Detection via Self-expression Model," is accepted in IEEE Symposium Series on Computational Intelligence (SSCI), 2016. [paper]

[06/09/2016] One paper "Lei Zhang and David Zhang, Evolutionary Cost-sensitive Extreme Learning Machine," is accepted as regular paper in IEEE Transactions on Neural Networks and Learning Systems, 2016. [paper], [code is available], [link]

[31/08/2016] 2 papers are accepted in ELM2016.

[30/08/2016] One paper "Zehui Zhan, Lei Zhang, Hu Mei, and Patrick S.W. Fong, Online Learners' Reading Ability Detection based on Eye-tracking Sensors," is published in Sensors, vol. 16, no. 9, pp. 1457-1473, 2016. [paper and code are available]

[29/08/2016] One paper "Lei Zhang and Yan Liu, Domain Regularized Transfer Component Analysis," is accepted in IEEE TENCON, 2016.

[26/07/2016] Our paper "Lei Zhang and David Zhang, Efficient Solutions for Discretenss, Drift and Disturbance (3D) in Electronic Olfaction," is accepted as regular paper in IEEE Transactions on Systems, Man, and Cybernetics: Part A, 2016. [paper], [code]

[07/07/2016] I will serve as the Best Paper Award Committee Chair in International Conference on ELM 2016, Singapore.

[24/06/2016] Our paper "Lei Zhang and David Zhang, Robust Visual Knowledge Transfer via Extreme Learning Machine based Domain Adaptation," is accepted as a regular paper by IEEE Transactions on Image Processing, 2016. [paper], [code]

[05/05/2016] Our paper "Fengchun Tian, Zhifang Liang, Lei Zhang, A novel pattern mismatch based interference elimination technique in E-nose," is published in Sensors and Actuators B: Chemical, vol. 234, pp. 703-712, 2016. [paper],[code]

[26/04/2016] I have been awarded as the Outstanding Reviewer for Sensor Review (2016 award for excellence in the Emerald Literati Network), two reviewers are chosen per year.

[05/04/2016] Our paper "Lei Zhang, David Zhang, Xin Yin, and Yan Liu, A Novel Semi-supervised Learning Approach in Artificial Olfaction for E-Nose Application," is published in IEEE Sensors Journal, vol. 16, no. 12, pp. 4919-4931, 2016.[paper], [code]

[15/03/2016] Our paper "Lei Zhang, Sunil Kr. Jha, and Tao Liu, Discriminative Kernel Transfer Learning via l2,1-Norm Minimization," is accepted in IEEE International Joint Conference on Neural Networks (IJCNN2016), 2016.[paper], [code], coming soon

[04/01/2016] Our paper "Lei Zhang, Wangmeng Zuo, and David Zhang, LSDT: Latent Sparse Domain Transfer Learning for Visual Adaptation," is published in IEEE Transactions on Image Processing, vol. 25, no. 3, pp. 1177-1191, 2016.[paper], [code],[code is available]

[23/12/2015] Our paper "Xin Yin,Lei Zhang*, Fengchun Tian, and David Zhang, Temperature Modulated Gas Sensing E-nose System for Low-cost and Fast Detection," is published in IEEE Sensors Journal, vol.16, no.2, pp. 464-474, 2016.[paper], [data and code] [paper, data and code are available]

[19/12/2015] Our paper "Lei Zhang, David Zhang, and Fengchun Tian, SVM and ELM: Who Wins? Object Recognition with Deep Convolutional Features from ImageNet" has been oral presented in The 6th Int'Conf ELM, 14-17,Dec 2015, Hangzhou.[paper, data and code are available. This paper has been recommended to publish in Neurocomputing, 2016.]

[15/12/2015] Our paper "Lei Zhang and David Zhang, MetricFusion: Generalized Metric Swarm Learning for Similarity Measure" is published in Information Fusion, vol. 30, pp. 80-90, 2016.[paper]

[10/12/2015] Our paper "Lei Zhang and David Zhang, Visual Understanding via Multi-Feature Shared Learning with Global Consistency" is published in IEEE Transactions on Multimedia (TMM), vol. 18, no. 2, pp. 247-259, 2016.[paper],[code is available]

[news] Our paper "Lei Zhang and David Zhang, Domain Adaptation Extreme Learning Machines for Drift Compensation in E-nose Systems" has been published in IEEE Transactions on Instrumentation and Measurement (TIM), vol. 64, no. 7, pp. 1790-1801, July 2015." [paper],[website]

[news] Our paper "Xiongwei Peng, Lei Zhang*, Fengchun Tian, and David Zhang, A novel sensor feature extraction based on kernel entropy component analysis for discrimination of indoor air contaminants" is published in Sensors and Actuators A, vol.234, pp. 143-149, 2015.[paper], [source code 1],[source code 2]

,[code is available]

[news] Our paper "Lei Zhang and Xiongwei Peng,Time series estimation of gas sensor baseline drift using ARMA and Kalman based models" is published in Sensor Review, vol.36, no.1, pp.34-39, 2016.

[21/11/2015] I have been invited as Session Chair for ELM2015, organized by NTU(Singapore), Tsinghua Univ and Zhejiang Univ.

[10/10/2015] I have been invited as Technical Program Committee for 2015 IEEE Symposium on Computational Intelligence and Ensemble Learning (IEEE CIEL2015).

[news] I have received the Excellent Doctoral Dissertation Award of Chongqing, China, 2015.

[Call for papers] I have organized a Special Session (Chair: Dr. Lei Zhang) on "Transfer Learning and Signal Processing for Multimedia Analysis," in IEEE SCOPES 2016, Oct 3-5, India. Welcome to submit your new research papers. Submission Deadline: Aug 25, 2016; Notice of Acceptance: Sep 10 2016.

[Call for papers] I have organized a Special Session (Chair: Dr. Lei Zhang and Dr. Sunil Kr. Jha) on "Advanced Learning for Large-scale Heterogeneous Data in Intelligent Vision and Olfaction Systems" in IEEE SSCI 2016, Dec 6-9, Athens, Greece. Welcome to submit your new research papers. Submission Deadline: Aug 1, 2016; Notice of Acceptance: Sep 12, 2016.

[Call for papers] I have organized a Special Session (SS-16, Chair: Dr. Lei Zhang) on "Intelligent Sensing Systems and Algorithms" in IEEE IS3C2016, Jul 4-6, Xi'an, China. Welcome to submit your new research papers. Paper Submission Deadline: 5 May 2016; Notice of Acceptance: 15 May 2016; Final Manuscripts Submission: 20 May 2016.

[Call for papers] I have organized a Special Session (SS-8, Chair: Dr. Lei Zhang) on "Computer Vision and Machine Learning" in IEEE TENCON2016, Nov 22-25, Singapore. Welcome to submit your new research papers. Paper Submission Deadline: 30 May 2016; Notice of Acceptance: 1 Aug 2016; Final Manuscripts Submission: 10 September 2016.

Full publications list