2019 - IEEE Fellow For contributions to geometric and image-based modeling
2018 - ACM Distinguished Member
The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Pattern recognition, Convolutional neural network and Salience. His study in Feature extraction, Artificial neural network, Image, Object and Deep learning are all subfields of Artificial intelligence. His Feature extraction research includes themes of Kadir–Brady saliency detector and Representation.
The concepts of his Pattern recognition study are interwoven with issues in Contextual image classification and Feature. The Convolutional neural network study combines topics in areas such as RGB color model and Image. In his study, Salient and Segmentation-based object categorization is strongly linked to Object detection, which falls under the umbrella field of Image segmentation.
His primary scientific interests are in Artificial intelligence, Computer vision, Pattern recognition, Convolutional neural network and Image. His Artificial intelligence study frequently links to related topics such as Machine learning. As a part of the same scientific family, Yizhou Yu mostly works in the field of Computer vision, focusing on Computer graphics and, on occasion, Algorithm.
His study in Pattern recognition is interdisciplinary in nature, drawing from both Artificial neural network, Object detection and Contextual image classification. His Convolutional neural network study combines topics from a wide range of disciplines, such as Benchmark and Salience. His research integrates issues of Salient and Saliency map in his study of Salience.
Yizhou Yu focuses on Artificial intelligence, Pattern recognition, Convolutional neural network, Segmentation and Image. He interconnects Computer vision and Natural language processing in the investigation of issues within Artificial intelligence. In general Pattern recognition study, his work on Discriminative model and Image segmentation often relates to the realm of Domain and Consistency, thereby connecting several areas of interest.
His research on Convolutional neural network also deals with topics like
His main research concerns Artificial intelligence, Pattern recognition, Convolutional neural network, Feature and Computer vision. Artificial intelligence is closely attributed to Natural language processing in his work. His work on Segmentation and Transduction is typically connected to Class and Domain as part of general Pattern recognition study, connecting several disciplines of science.
Within one scientific family, Yizhou Yu focuses on topics pertaining to Robustness under Convolutional neural network, and may sometimes address concerns connected to Pyramid, Adversarial system, Image segmentation and Artificial neural network. His Pyramid study, which is part of a larger body of work in Feature, is frequently linked to Volume, bridging the gap between disciplines. His Computer vision study integrates concerns from other disciplines, such as X ray diagnosis and Identification.
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.
Efficient View-Dependent Image-Based Rendering with Projective Texture-Mapping
Paul Debevec;Yizhou Yu;George Boshokov.
eurographics (1998)
Mesh editing with poisson-based gradient field manipulation
Yizhou Yu;Kun Zhou;Dong Xu;Xiaohan Shi.
international conference on computer graphics and interactive techniques (2004)
Inverse global illumination: recovering reflectance models of real scenes from photographs
Yizhou Yu;Paul Debevec;Jitendra Malik;Tim Hawkins.
international conference on computer graphics and interactive techniques (1999)
Visual saliency based on multiscale deep features
Guanbin Li;Yizhou Yu.
computer vision and pattern recognition (2015)
Deep Contrast Learning for Salient Object Detection
Guanbin Li;Yizhou Yu.
computer vision and pattern recognition (2016)
HD-CNN: Hierarchical Deep Convolutional Neural Networks for Large Scale Visual Recognition
Zhicheng Yan;Hao Zhang;Robinson Piramuthu;Vignesh Jagadeesh.
international conference on computer vision (2015)
Feature matching and deformation for texture synthesis
Qing Wu;Yizhou Yu.
international conference on computer graphics and interactive techniques (2004)
Particle-based simulation of granular materials
Nathan Bell;Yizhou Yu;Peter J. Mucha.
symposium on computer animation (2005)
Recovering photometric properties of architectural scenes from photographs
Yizhou Yu;Jitendra Malik.
international conference on computer graphics and interactive techniques (1998)
Visual Saliency Detection Based on Multiscale Deep CNN Features
Guanbin Li;Yizhou Yu.
IEEE Transactions on Image Processing (2016)
Profile was last updated on December 6th, 2021.
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