The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Computer vision, Image retrieval and Feature extraction. His study involves Visual Word, Object, Visualization, Tracking and Hidden Markov model, a branch of Artificial intelligence. His work investigates the relationship between Pattern recognition and topics such as Eye tracking that intersect with problems in Unsupervised learning.
His Video tracking, Image processing and Gaussian blur study in the realm of Computer vision interacts with subjects such as Source code. Wengang Zhou combines subjects such as Full text search, Quantization, Information retrieval and Spatial contextual awareness with his study of Image retrieval. His study in Feature extraction is interdisciplinary in nature, drawing from both Discriminative model and Feature.
His primary scientific interests are in Artificial intelligence, Pattern recognition, Computer vision, Image retrieval and Feature extraction. Many of his research projects under Artificial intelligence are closely connected to Frame and Sign language with Frame and Sign language, tying the diverse disciplines of science together. He works mostly in the field of Visual Word, limiting it down to concerns involving Automatic image annotation and, occasionally, Image texture.
The study incorporates disciplines such as Artificial neural network, Image, Quantization and Cluster analysis in addition to Pattern recognition. His work in the fields of Computer vision, such as Tracking, Video tracking and Scale-invariant feature transform, overlaps with other areas such as Matching. Wengang Zhou has included themes like Codebook, Data mining, Spatial contextual awareness and Information retrieval, Search engine indexing in his Image retrieval study.
His scientific interests lie mostly in Artificial intelligence, Computer vision, Pattern recognition, Feature learning and Feature extraction. He performs multidisciplinary studies into Artificial intelligence and Frame in his work. As part of the same scientific family, he usually focuses on Computer vision, concentrating on Benchmark and intersecting with Data mining, Tree and Optical flow.
His work on Discriminative model and Segmentation as part of general Pattern recognition research is often related to Sign language, Regression and Solver, thus linking different fields of science. His Feature learning study combines topics in areas such as Natural language processing, Unsupervised learning, State and Reinforcement learning. The Feature extraction study combines topics in areas such as Regularization, Feature and Visualization.
Wengang Zhou mainly focuses on Artificial intelligence, Computer vision, Deep learning, Eye tracking and Feature extraction. His study ties his expertise on Pattern recognition together with the subject of Artificial intelligence. His work on Tracking and Segmentation as part of general Computer vision research is frequently linked to Frame, thereby connecting diverse disciplines of science.
His Deep learning research also works with subjects such as
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.
The Visual Object Tracking VOT2017 Challenge Results
Matej Kristan;Ales Leonardis;Jiri Matas;Michael Felsberg.
international conference on computer vision (2017)
Active contours with selective local or global segmentation: A new formulation and level set method
Kaihua Zhang;Lei Zhang;Huihui Song;Wengang Zhou.
Image and Vision Computing (2010)
The sixth visual object tracking VOT2018 challenge results
Matej Kristan;Aleš Leonardis;Jiří Matas;Michael Felsberg.
european conference on computer vision (2019)
Spatial coding for large scale partial-duplicate web image search
Wengang Zhou;Yijuan Lu;Houqiang Li;Yibing Song.
acm multimedia (2010)
Picking Deep Filter Responses for Fine-Grained Image Recognition
Xiaopeng Zhang;Hongkai Xiong;Wengang Zhou;Weiyao Lin.
computer vision and pattern recognition (2016)
Principal Visual Word Discovery for Automatic License Plate Detection
Wengang Zhou;Houqiang Li;Yijuan Lu;Qi Tian.
IEEE Transactions on Image Processing (2012)
Multi-cue Correlation Filters for Robust Visual Tracking
Ning Wang;Wengang Zhou;Qi Tian;Richang Hong.
computer vision and pattern recognition (2018)
Sign Language Recognition using 3D convolutional neural networks
Jie Huang;Wengang Zhou;Houqiang Li;Weiping Li.
international conference on multimedia and expo (2015)
Video-based Sign Language Recognition without Temporal Segmentation
Jie Huang;Wengang Zhou;Qilin Zhang;Houqiang Li.
national conference on artificial intelligence (2018)
Incorporating BERT into Neural Machine Translation
Jinhua Zhu;Yingce Xia;Lijun Wu;Di He.
international conference on learning representations (2020)
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