H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 42 Citations 6,513 174 World Ranking 4187 National Ranking 391

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

Jianzhuang Liu mainly investigates Artificial intelligence, Pattern recognition, Computer vision, Algorithm and Facial recognition system. His work on Artificial intelligence is being expanded to include thematically relevant topics such as Point. His work carried out in the field of Pattern recognition brings together such families of science as Convolution and Deep learning.

His Computer vision research includes themes of Computational geometry and Sparse approximation. His research in Algorithm intersects with topics in Constrained clustering, Graph theory, Mathematical optimization, Bounding overwatch and Real image. His Facial recognition system research incorporates themes from Gabor filter and Invariant.

His most cited work include:

  • Local Derivative Pattern Versus Local Binary Pattern: Face Recognition With High-Order Local Pattern Descriptor (780 citations)
  • Robust 3D Face Recognition by Local Shape Difference Boosting (155 citations)
  • 2D Shape Matching by Contour Flexibility (153 citations)

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

Jianzhuang Liu focuses on Artificial intelligence, Pattern recognition, Computer vision, Object and Image. His work is dedicated to discovering how Artificial intelligence, Machine learning are connected with Classifier and other disciplines. His Pattern recognition study incorporates themes from Facial recognition system, Feature and Benchmark.

He has researched Facial recognition system in several fields, including Cognitive neuroscience of visual object recognition and Linear discriminant analysis. His biological study deals with issues like Sketch, which deal with fields such as Visual Word. The study incorporates disciplines such as Pixel and Moiré pattern in addition to Image.

He most often published in these fields:

  • Artificial intelligence (87.38%)
  • Pattern recognition (41.59%)
  • Computer vision (37.85%)

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

  • Artificial intelligence (87.38%)
  • Pattern recognition (41.59%)
  • Computer vision (37.85%)

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

The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Computer vision, Convolutional neural network and Machine learning. He merges Artificial intelligence with Process in his research. His study in Pattern recognition is interdisciplinary in nature, drawing from both Perspective, Similarity, Feature and Benchmark.

His work in Computer vision addresses issues such as Matching, which are connected to fields such as Contrast and End-to-end principle. His Convolutional neural network study also includes fields such as

  • Backpropagation and related Circulant matrix, Filter, Algorithm, Projection and Stochastic gradient descent,
  • Epipolar geometry, which have a strong connection to Image warping and Light field. His research integrates issues of Bayesian probability and Bayesian inference in his study of Machine learning.

Between 2018 and 2021, his most popular works were:

  • Multinomial Distribution Learning for Effective Neural Architecture Search (43 citations)
  • Circulant Binary Convolutional Networks: Enhancing the Performance of 1-Bit DCNNs With Circulant Back Propagation (41 citations)
  • Projection Convolutional Neural Networks for 1-bit CNNs via Discrete Back Propagation (37 citations)

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

  • Artificial intelligence
  • Machine learning
  • Computer vision

His primary areas of investigation include Artificial intelligence, Pattern recognition, Convolutional neural network, Process and Artificial neural network. His Artificial intelligence research is multidisciplinary, relying on both Machine learning and Computer vision. His Computer vision research incorporates elements of Data modeling, Key and Training set.

The Pattern recognition study combines topics in areas such as Image, Translation and Resolution. Projection, Filter, Circulant matrix and Algorithm is closely connected to Backpropagation in his research, which is encompassed under the umbrella topic of Convolutional neural network. He combines subjects such as Channel, Differentiable function and Reduction with his study of Artificial neural network.

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

Local Derivative Pattern Versus Local Binary Pattern: Face Recognition With High-Order Local Pattern Descriptor

Baochang Zhang;Yongsheng Gao;Sanqiang Zhao;Jianzhuang Liu.
IEEE Transactions on Image Processing (2010)

1075 Citations

2D Shape Matching by Contour Flexibility

Chunjing Xu;Jianzhuang Liu;Xiaoou Tang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)

237 Citations

Robust 3D Face Recognition by Local Shape Difference Boosting

Yueming Wang;Jianzhuang Liu;Xiaoou Tang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2010)

218 Citations

Gabor Convolutional Networks

Shangzhen Luan;Chen Chen;Baochang Zhang;Jungong Han.
IEEE Transactions on Image Processing (2018)

190 Citations

A spatial-temporal approach for video caption detection and recognition

Xiaoou Tang;Xinbo Gao;Jianzhuang Liu;Hongjiang Zhang.
IEEE Transactions on Neural Networks (2002)

179 Citations

Pairwise constraint propagation by semidefinite programming for semi-supervised classification

Zhenguo Li;Jianzhuang Liu;Xiaoou Tang.
international conference on machine learning (2008)

150 Citations

Hidden Factor Analysis for Age Invariant Face Recognition

Dihong Gong;Zhifeng Li;Dahua Lin;Jianzhuang Liu.
international conference on computer vision (2013)

143 Citations

Constrained clustering via spectral regularization

Zhenguo Li;Jianzhuang Liu;Xiaoou Tang.
computer vision and pattern recognition (2009)

133 Citations

Graph-based method for face identification from a single 2D line drawing

Jianzhuang Liu;Yong Tsui Lee.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2001)

130 Citations

A comparison of 3D shape retrieval methods based on a large-scale benchmark supporting multimodal queries

Bo Li;Yijuan Lu;Chunyuan Li;Afzal Godil.
Computer Vision and Image Understanding (2015)

127 Citations

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Best Scientists Citing Jianzhuang Liu

Baochang Zhang

Baochang Zhang

Beihang University

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Dacheng Tao

Dacheng Tao

University of Sydney

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École Centrale de Lyon

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Xuelong Li

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Northwestern Polytechnical University

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Xinbo Gao

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Chongqing University of Posts and Telecommunications

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Qixiang Ye

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Chinese Academy of Sciences

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Yongsheng Gao

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Griffith University

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Tsinghua University

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Beihang University

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Rongrong Ji

Rongrong Ji

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Nannan Wang

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