2022 - Research.com Computer Science in China Leader Award
His main research concerns Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Sparse approximation. In his work, Data mining is strongly intertwined with Machine learning, which is a subfield of Artificial intelligence. Lei Zhang focuses mostly in the field of Pattern recognition, narrowing it down to topics relating to Image and, in certain cases, Noise reduction.
His research integrates issues of Norm and Dimensionality reduction in his study of Facial recognition system. Lei Zhang has included themes like Matching and Orientation in his Biometrics study. The various areas that Lei Zhang examines in his Image resolution study include Kernel and Superresolution.
His primary scientific interests are in Artificial intelligence, Pattern recognition, Computer vision, Optoelectronics and Optics. His study ties his expertise on Machine learning together with the subject of Artificial intelligence. His work carried out in the field of Pattern recognition brings together such families of science as Pixel, Facial recognition system and Feature.
Lei Zhang studies Computer vision, namely Biometrics. Fiber laser and Laser are the primary areas of interest in his Optics study.
His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Computer vision, Deep learning and Convolutional neural network. His Artificial intelligence study frequently draws parallels with other fields, such as Machine learning. Feature learning is the focus of his Machine learning research.
Lei Zhang has researched Pattern recognition in several fields, including Pixel and Benchmark. His studies link Code with Artificial neural network.
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Deep learning, Feature extraction and Computer vision. He frequently studies issues relating to Machine learning and Artificial intelligence. His work deals with themes such as Image resolution and Benchmark, which intersect with Machine learning.
His biological study spans a wide range of topics, including Ground truth, Normalization, Pooling and Metric. His Deep learning research includes elements of Normalization, Statistical physics, Algorithm and Identification. Lei Zhang has included themes like Mixture model, Nonlinear dimensionality reduction, Subspace topology and Robustness in his Feature extraction study.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
FSIM: A Feature Similarity Index for Image Quality Assessment
Lin Zhang;Lei Zhang;Xuanqin Mou;D. Zhang.
IEEE Transactions on Image Processing (2011)
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
Kai Zhang;Wangmeng Zuo;Yunjin Chen;Deyu Meng.
IEEE Transactions on Image Processing (2017)
Fast Compressive Tracking
Kaihua Zhang;Lei Zhang;Ming-Hsuan Yang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2014)
Sparse representation or collaborative representation: Which helps face recognition?
Lei Zhang;Meng Yang;Xiangchu Feng.
international conference on computer vision (2011)
A Completed Modeling of Local Binary Pattern Operator for Texture Classification
Zhenhua Guo;Lei Zhang;David Zhang.
IEEE Transactions on Image Processing (2010)
Real-time compressive tracking
Kaihua Zhang;Lei Zhang;Ming-Hsuan Yang.
european conference on computer vision (2012)
The Visual Object Tracking VOT2017 Challenge Results
Matej Kristan;Ales Leonardis;Jiri Matas;Michael Felsberg.
international conference on computer vision (2017)
Active contours driven by local image fitting energy
Kaihua Zhang;Huihui Song;Lei Zhang.
Pattern Recognition (2010)
Image Deblurring and Super-Resolution by Adaptive Sparse Domain Selection and Adaptive Regularization
Weisheng Dong;Lei Zhang;Guangming Shi;Xiaolin Wu.
IEEE Transactions on Image Processing (2011)
Nonlocally Centralized Sparse Representation for Image Restoration
Weisheng Dong;Lei Zhang;Guangming Shi;Xin Li.
IEEE Transactions on Image Processing (2013)
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