Jue Wang spends much of his time researching Artificial intelligence, Computer vision, Kernel, Pattern recognition and Deblurring. Artificial intelligence is closely attributed to Smoothing in his study. Many of his studies involve connections with topics such as Computer graphics and Computer vision.
The concepts of his Kernel study are interwoven with issues in Deconvolution, Image restoration and Mean-shift. His studies in Pattern recognition integrate themes in fields like Smoothness and Feature detection. His Deblurring research is multidisciplinary, incorporating elements of Salient and Motion blur.
Jue Wang mainly focuses on Artificial intelligence, Computer vision, Pattern recognition, Image and Deblurring. Kernel, Segmentation, Pixel, Image restoration and Object are the core of his Artificial intelligence study. His research on Computer vision often connects related areas such as Computer graphics.
His study looks at the relationship between Pattern recognition and topics such as Feature, which overlap with Subspace topology and Image stabilization. His work on Image editing as part of general Image study is frequently connected to Task, Alpha and Process, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. Jue Wang has included themes like Deconvolution, Kernel density estimation and Motion blur in his Deblurring study.
Jue Wang mostly deals with Artificial intelligence, Computer vision, Image, Deep learning and Pattern recognition. Artificial intelligence is represented through his Artificial neural network, Noise reduction, Unsupervised learning, Feature and Homography research. His Computer vision study frequently intersects with other fields, such as Flow.
His research integrates issues of Embedding and Information retrieval in his study of Image. Jue Wang works mostly in the field of Deep learning, limiting it down to topics relating to Point cloud and, in certain cases, Topology and Feature learning, as a part of the same area of interest. The various areas that Jue Wang examines in his Pattern recognition study include Pixel, Image translation and Colors of noise.
His primary areas of investigation include Artificial intelligence, Computer vision, Image, Deep learning and Real image. Jue Wang integrates several fields in his works, including Artificial intelligence and Training. His research in Computer vision intersects with topics in Convolution and Resolution.
His Image research incorporates elements of Pixel, Noise reduction and Pattern recognition. As part of one scientific family, he deals mainly with the area of Deep learning, narrowing it down to issues related to the Algorithm, and often Feature learning and Topology. His Real image research includes elements of Channel, Estimator, Benchmark, sRGB and Impulse noise.
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.
Video SnapCut: robust video object cutout using localized classifiers
Xue Bai;Jue Wang;David Simons;Guillermo Sapiro.
international conference on computer graphics and interactive techniques (2009)
Interactive video cutout
Jue Wang;Pravin Bhat;R. Alex Colburn;Maneesh Agrawala.
international conference on computer graphics and interactive techniques (2005)
Investigating Haze-Relevant Features in a Learning Framework for Image Dehazing
Ketan Tang;Jianchao Yang;Jue Wang.
computer vision and pattern recognition (2014)
Optimized Color Sampling for Robust Matting
Jue Wang;M.F. Cohen.
computer vision and pattern recognition (2007)
Image and video matting: a survey
Jue Wang;Michael F. Cohen.
Foundations and Trends in Computer Graphics and Vision (2007)
An iterative optimization approach for unified image segmentation and matting
J. Wang;M.F. Cohen.
international conference on computer vision (2005)
Edge-based blur kernel estimation using patch priors
Libin Sun;Sunghyun Cho;Jue Wang;J. Hays.
international conference on computational photography (2013)
Subspace video stabilization
Feng Liu;Michael Gleicher;Jue Wang;Hailin Jin.
ACM Transactions on Graphics (2011)
Jue Wang;Yingqing Xu;Heung-Yeung Shum;Michael F. Cohen.
international conference on computer graphics and interactive techniques (2004)
Image and Video Segmentation by Anisotropic Kernel Mean Shift
Jue Wang;Bo Thiesson;Yingqing Xu;Michael F. Cohen.
european conference on computer vision (2004)
Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: