H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 42 Citations 14,025 113 World Ranking 4190 National Ranking 9

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Computer vision

Shengcai Liao mainly investigates Artificial intelligence, Pattern recognition, Computer vision, Facial recognition system and Face detection. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning and Deviance. His study in the field of Discriminative model and AdaBoost also crosses realms of Metric.

His work deals with themes such as Representation and Color term, which intersect with Computer vision. His studies deal with areas such as Discriminant, Quadratic classifier and Identification as well as Representation. His Facial recognition system study is concerned with Face in general.

His most cited work include:

  • Person re-identification by Local Maximal Occurrence representation and metric learning (1417 citations)
  • Learning Face Representation from Scratch (1003 citations)
  • Deep Metric Learning for Person Re-identification (516 citations)

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

His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Computer vision, Facial recognition system and Machine learning. Feature, Feature extraction, Convolutional neural network, Discriminative model and Face are among the areas of Artificial intelligence where Shengcai Liao concentrates his study. The various areas that Shengcai Liao examines in his Pattern recognition study include Pixel, Face detection, Subspace topology and Histogram.

The Object detection, Object-class detection and Video tracking research Shengcai Liao does as part of his general Computer vision study is frequently linked to other disciplines of science, such as Matching, therefore creating a link between diverse domains of science. His Facial recognition system study which covers Biometrics that intersects with Pattern recognition. His Re identification study in the realm of Machine learning interacts with subjects such as Metric and Code.

He most often published in these fields:

  • Artificial intelligence (89.23%)
  • Pattern recognition (56.92%)
  • Computer vision (34.62%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (89.23%)
  • Machine learning (23.85%)
  • Pattern recognition (56.92%)

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

Artificial intelligence, Machine learning, Pattern recognition, Code and Pedestrian detection are his primary areas of study. In his work, k-nearest neighbors algorithm is strongly intertwined with State, which is a subfield of Artificial intelligence. Shengcai Liao usually deals with Machine learning and limits it to topics linked to Training set and Texture mapping and Re identification.

His Pattern recognition research incorporates elements of Pixel and Consistency. His Consistency research is multidisciplinary, incorporating elements of Facial recognition system, Parsing, Single image and Texture transfer. He studied Feature and Feature extraction that intersect with Image, Pyramid and Object.

Between 2019 and 2021, his most popular works were:

  • Vehicle Re-Identification Using Quadruple Directional Deep Learning Features (50 citations)
  • Unsupervised Domain Adaptation with Noise Resistible Mutual-Training for Person Re-identification (15 citations)
  • Pedestrian Detection: The Elephant In The Room (11 citations)

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

  • Artificial intelligence
  • Machine learning
  • Computer vision

Shengcai Liao mostly deals with Artificial intelligence, Machine learning, Code, Training and Feature. His is involved in several facets of Artificial intelligence study, as is seen by his studies on Feature learning and Representation. His work on Instance selection and Cluster analysis as part of general Machine learning study is frequently linked to Domain adaptation and Divergence, therefore connecting diverse disciplines of science.

His work in Code incorporates the disciplines of Pedestrian detection, Ranging, Pipeline, Detector and Data mining. Throughout his Training studies, Shengcai Liao incorporates elements of other sciences such as Texture mapping, Re identification, Camera network, Training set and Clothing. His studies in Feature integrate themes in fields like Transfer of learning, Convolution and Pooling.

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.

Best Publications

Person re-identification by Local Maximal Occurrence representation and metric learning

Shengcai Liao;Yang Hu;Xiangyu Zhu;Stan Z. Li.
computer vision and pattern recognition (2015)

1516 Citations

Learning Face Representation from Scratch

Dong Yi;Zhen Lei;Shengcai Liao;Stan Z. Li.
arXiv: Computer Vision and Pattern Recognition (2014)

1232 Citations

Deep Metric Learning for Person Re-identification

Dong Yi;Zhen Lei;Shengcai Liao;Stan Z. Li.
international conference on pattern recognition (2014)

775 Citations

Learning multi-scale block local binary patterns for face recognition

Shengcai Liao;Xiangxin Zhu;Zhen Lei;Lun Zhang.
international conference on biometrics (2007)

683 Citations

Illumination Invariant Face Recognition Using Near-Infrared Images

S.Z. Li;RuFeng Chu;ShengCai Liao;Lun Zhang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

663 Citations

Face detection based on multi-block LBP representation

Lun Zhang;Rufeng Chu;Shiming Xiang;Shengcai Liao.
international conference on biometrics (2007)

484 Citations

Salient Color Names for Person Re-identification

Yang Yang;Jimei Yang;Junjie Yan;Shengcai Liao.
european conference on computer vision (2014)

449 Citations

Modeling pixel process with scale invariant local patterns for background subtraction in complex scenes

Shengcai Liao;Guoying Zhao;Vili Kellokumpu;Matti Pietikainen.
computer vision and pattern recognition (2010)

411 Citations

Partial face recognition: An alignment free approach

Shengcai Liao;Anil K. Jain.
International Journal of Central Banking (2011)

338 Citations

Partial Face Recognition: Alignment-Free Approach

Shengcai Liao;A. K. Jain;S. Z. Li.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2013)

336 Citations

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Best Scientists Citing Shengcai Liao

Stan Z. Li

Stan Z. Li

Chinese Academy of Sciences

Publications: 111

Zhen Lei

Zhen Lei

Chinese Academy of Sciences

Publications: 88

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 65

Wei-Shi Zheng

Wei-Shi Zheng

Sun Yat-sen University

Publications: 64

Anil K. Jain

Anil K. Jain

Michigan State University

Publications: 61

Rama Chellappa

Rama Chellappa

Johns Hopkins University

Publications: 57

Ran He

Ran He

Chinese Academy of Sciences

Publications: 52

Liang Zheng

Liang Zheng

Australian National University

Publications: 50

Yi Yang

Yi Yang

Zhejiang University

Publications: 50

Xiaogang Wang

Xiaogang Wang

Chinese University of Hong Kong

Publications: 48

Jianhuang Lai

Jianhuang Lai

Sun Yat-sen University

Publications: 47

Jiwen Lu

Jiwen Lu

Tsinghua University

Publications: 44

Zhenan Sun

Zhenan Sun

Chinese Academy of Sciences

Publications: 43

Shaogang Gong

Shaogang Gong

Queen Mary University of London

Publications: 39

Weihong Deng

Weihong Deng

Beijing University of Posts and Telecommunications

Publications: 38

Yunhong Wang

Yunhong Wang

Beihang University

Publications: 36

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