His primary scientific interests are in Artificial intelligence, Facial recognition system, Pattern recognition, Computer vision and Face. His Artificial intelligence study frequently draws parallels with other fields, such as Machine learning. His Facial recognition system study combines topics in areas such as Image processing, Gabor filter, Facial expression and Subspace topology.
His work on Linear discriminant analysis as part of general Pattern recognition research is often related to Gabor wavelet, thus linking different fields of science. His work in the fields of Computer vision, such as Local binary patterns, Histogram and Preprocessor, intersects with other areas such as Set. Shiguang Shan has researched Face in several fields, including Text mining, Pose, Similarity and Database.
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Facial recognition system, Computer vision and Face. His study looks at the relationship between Artificial intelligence and fields such as Machine learning, as well as how they intersect with chemical problems. His Pattern recognition research is multidisciplinary, incorporating elements of Contextual image classification, Histogram and Robustness.
His study in Facial recognition system is interdisciplinary in nature, drawing from both Image processing, Subspace topology, Facial expression and Biometrics. Computer vision is closely attributed to AdaBoost in his research. His work carried out in the field of Face brings together such families of science as Speech recognition and Representation.
His main research concerns Artificial intelligence, Pattern recognition, Face, Computer vision and Discriminative model. His work on Feature extraction, Facial recognition system and Feature as part of general Artificial intelligence study is frequently connected to Task analysis, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. He has included themes like Training set and Robustness in his Facial recognition system study.
His work on Feature learning as part of general Pattern recognition research is frequently linked to Set, bridging the gap between disciplines. His biological study spans a wide range of topics, including End-to-end principle, Generator and Expression. His work on Image as part of general Computer vision research is frequently linked to Frame, thereby connecting diverse disciplines of science.
Shiguang Shan mainly focuses on Artificial intelligence, Pattern recognition, Face, Facial recognition system and Feature extraction. His Artificial intelligence study frequently draws connections between adjacent fields such as Computer vision. His work in the fields of Segmentation overlaps with other areas such as Set.
His Face research includes elements of Representation and Image. His Facial recognition system study integrates concerns from other disciplines, such as Normalization, Sketch recognition and Invariant. His research investigates the connection between Feature extraction and topics such as Scene graph that intersect with issues in Intersection, Cognitive neuroscience of visual object recognition and Visual reasoning.
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.
Local Gabor binary pattern histogram sequence (LGBPHS): a novel non-statistical model for face representation and recognition
Wenchao Zhang;Shiguang Shan;Wen Gao;Xilin Chen.
international conference on computer vision (2005)
The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations
Wen Gao;Bo Cao;Shiguang Shan;Xilin Chen.
systems man and cybernetics (2008)
WLD: A Robust Local Image Descriptor
Jie Chen;Shiguang Shan;Chu He;Guoying Zhao.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2010)
Histogram of Gabor Phase Patterns (HGPP): A Novel Object Representation Approach for Face Recognition
Baochang Zhang;Shiguang Shan;Xilin Chen;Wen Gao.
IEEE Transactions on Image Processing (2007)
Coarse-to-Fine Auto-Encoder Networks (CFAN) for Real-Time Face Alignment
Jie Zhang;Shiguang Shan;Meina Kan;Xilin Chen.
european conference on computer vision (2014)
Deep Supervised Hashing for Fast Image Retrieval
Haomiao Liu;Ruiping Wang;Shiguang Shan;Xilin Chen.
computer vision and pattern recognition (2016)
Multi-View Discriminant Analysis
Meina Kan;Shiguang Shan;Haihong Zhang;Shihong Lao.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2016)
Manifold-Manifold Distance with application to face recognition based on image set
Ruiping Wang;Shiguang Shan;Xilin Chen;Wen Gao.
computer vision and pattern recognition (2008)
Illumination normalization for robust face recognition against varying lighting conditions
Shiguang Shan;Wen Gao;Bo Cao;Debin Zhao.
international soi conference (2003)
Fusing Local Patterns of Gabor Magnitude and Phase for Face Recognition
Shufu Xie;Shiguang Shan;Xilin Chen;Jie Chen.
IEEE Transactions on Image Processing (2010)
Profile was last updated on December 6th, 2021.
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