H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 79 Citations 26,221 377 World Ranking 480 National Ranking 37

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

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.

His most cited work include:

  • Local Gabor binary pattern histogram sequence (LGBPHS): a novel non-statistical model for face representation and recognition (911 citations)
  • WLD: A Robust Local Image Descriptor (784 citations)
  • The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations (772 citations)

What are the main themes of his work throughout his whole career to date?

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.

He most often published in these fields:

  • Artificial intelligence (95.22%)
  • Pattern recognition (55.65%)
  • Facial recognition system (41.30%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (95.22%)
  • Pattern recognition (55.65%)
  • Face (30.22%)

In recent papers he was focusing on the following fields of study:

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.

Between 2018 and 2021, his most popular works were:

  • AttGAN: Facial Attribute Editing by Only Changing What You Want (224 citations)
  • Occlusion Aware Facial Expression Recognition Using CNN With Attention Mechanism (141 citations)
  • Interaction-And-Aggregation Network for Person Re-Identification (81 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Computer vision
  • Machine learning

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.

Top Publications

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)

1285 Citations

The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations

Wen Gao;Bo Cao;Shiguang Shan;Xilin Chen.
systems man and cybernetics (2008)

1111 Citations

WLD: A Robust Local Image Descriptor

Jie Chen;Shiguang Shan;Chu He;Guoying Zhao.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2010)

1067 Citations

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)

708 Citations

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)

594 Citations

Deep Supervised Hashing for Fast Image Retrieval

Haomiao Liu;Ruiping Wang;Shiguang Shan;Xilin Chen.
computer vision and pattern recognition (2016)

571 Citations

Multi-View Discriminant Analysis

Meina Kan;Shiguang Shan;Haihong Zhang;Shihong Lao.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2016)

566 Citations

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)

485 Citations

Illumination normalization for robust face recognition against varying lighting conditions

Shiguang Shan;Wen Gao;Bo Cao;Debin Zhao.
international soi conference (2003)

479 Citations

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)

443 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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