H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 69 Citations 16,202 295 World Ranking 909 National Ranking 76

Research.com Recognitions

Awards & Achievements

2020 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to human action recognition and applications

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Pattern recognition

Jiwen Lu mainly focuses on Artificial intelligence, Pattern recognition, Discriminative model, Feature extraction and Facial recognition system. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning, Metric and Computer vision. His Pattern recognition research incorporates themes from Subspace topology, Feature, Artificial neural network, Binary code and Deep learning.

His work carried out in the field of Discriminative model brings together such families of science as Semi-supervised learning, Image and Face. His Feature extraction study combines topics from a wide range of disciplines, such as Robustness and Feature vector. His research in Facial recognition system intersects with topics in Histogram, Linear discriminant analysis, Principal component analysis and Sparse approximation.

His most cited work include:

  • PCANet: A Simple Deep Learning Baseline for Image Classification? (690 citations)
  • Discriminative Deep Metric Learning for Face Verification in the Wild (481 citations)
  • Deep hashing for compact binary codes learning (406 citations)

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

Jiwen Lu spends much of his time researching Artificial intelligence, Pattern recognition, Feature extraction, Discriminative model and Computer vision. His Artificial intelligence research includes themes of Machine learning and Metric. The concepts of his Pattern recognition study are interwoven with issues in Subspace topology, Feature, Deep learning and Binary code.

Jiwen Lu interconnects Visualization, Histogram, Robustness and Biometrics in the investigation of issues within Feature extraction. He combines subjects such as Gait, Image, Representation and Feature vector with his study of Discriminative model. His biological study spans a wide range of topics, including Nonlinear dimensionality reduction and Pattern recognition.

He most often published in these fields:

  • Artificial intelligence (88.69%)
  • Pattern recognition (58.72%)
  • Feature extraction (31.50%)

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

  • Artificial intelligence (88.69%)
  • Pattern recognition (58.72%)
  • Machine learning (22.94%)

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

His main research concerns Artificial intelligence, Pattern recognition, Machine learning, Theoretical computer science and Feature extraction. His Artificial intelligence study frequently draws connections between related disciplines such as Computer vision. The concepts of his Pattern recognition study are interwoven with issues in Point cloud, Spectral clustering, Cluster analysis and Similarity.

His Theoretical computer science research is multidisciplinary, relying on both Graph, Graph based, Discriminative model and Graph. The Discriminative model study combines topics in areas such as Feature and Feature learning. His Feature extraction research incorporates themes from Artificial neural network, Semantics and Robustness.

Between 2019 and 2021, his most popular works were:

  • Structure-Preserving Super Resolution With Gradient Guidance (25 citations)
  • Deep Variational and Structural Hashing (18 citations)
  • Deep Face Super-Resolution With Iterative Collaboration Between Attentive Recovery and Landmark Estimation (11 citations)

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

  • Artificial intelligence
  • Machine learning
  • Computer vision

The scientist’s investigation covers issues in Artificial intelligence, Machine learning, Feature extraction, Algorithm and Benchmark. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Computer vision and Pattern recognition. His Pattern recognition research includes themes of False positive paradox and Pascal.

His work in Machine learning covers topics such as Metric which are related to areas like Generator, Decision boundary, Embedding and Training set. His research integrates issues of Discriminative model and Robustness in his study of Feature extraction. His Benchmark research incorporates elements of Binary code and Probabilistic logic.

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

PCANet: A Simple Deep Learning Baseline for Image Classification?

Tsung-Han Chan;Kui Jia;Shenghua Gao;Jiwen Lu.
IEEE Transactions on Image Processing (2015)

1072 Citations

Discriminative Deep Metric Learning for Face Verification in the Wild

Junlin Hu;Jiwen Lu;Yap-Peng Tan.
computer vision and pattern recognition (2014)

672 Citations

Deep hashing for compact binary codes learning

Venice Erin Liong;Jiwen Lu;Gang Wang;Pierre Moulin.
computer vision and pattern recognition (2015)

462 Citations

Discriminative Multimanifold Analysis for Face Recognition from a Single Training Sample per Person

Jiwen Lu;Yap-Peng Tan;Gang Wang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2013)

418 Citations

Neighborhood repulsed metric learning for kinship verification

Jiwen Lu;Junlin Hu;Xiuzhuang Zhou;Yuanyuan Shang.
computer vision and pattern recognition (2012)

399 Citations

A Siamese Long Short-Term Memory Architecture for Human Re-identification

Rahul Rama Varior;Bing Shuai;Jiwen Lu;Dong Xu.
european conference on computer vision (2016)

362 Citations

Learning Compact Binary Face Descriptor for Face Recognition

Jiwen Lu;Venice Erin Liong;Xiuzhuang Zhou;Jie Zhou.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2015)

331 Citations

Deep transfer metric learning

Junlin Hu;Jiwen Lu;Yap-Peng Tan.
computer vision and pattern recognition (2015)

260 Citations

Deep Transfer Metric Learning

Junlin Hu;Jiwen Lu;Yap-Peng Tan;Jie Zhou.
IEEE Transactions on Image Processing (2016)

259 Citations

Learning Compact Binary Descriptors with Unsupervised Deep Neural Networks

Kevin Lin;Jiwen Lu;Chu-Song Chen;Jie Zhou.
computer vision and pattern recognition (2016)

257 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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Top Scientists Citing Jiwen Lu

Dacheng Tao

Dacheng Tao

University of Sydney

Publications: 56

Ling Shao

Ling Shao

Inception Institute of Artificial Intelligence

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Xilin Chen

Xilin Chen

Institute Of Computing Technology

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Ran He

Ran He

Chinese Academy of Sciences

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Shiguang Shan

Shiguang Shan

Chinese Academy of Sciences

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Weihong Deng

Weihong Deng

Beijing University of Posts and Telecommunications

Publications: 36

Zhenan Sun

Zhenan Sun

Chinese Academy of Sciences

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Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 30

Fumin Shen

Fumin Shen

University of Electronic Science and Technology of China

Publications: 30

Xiao-Yuan Jing

Xiao-Yuan Jing

Wuhan University

Publications: 30

Rama Chellappa

Rama Chellappa

Johns Hopkins University

Publications: 29

Yun Fu

Yun Fu

Northeastern University

Publications: 29

Richa Singh

Richa Singh

Indian Institute of Technology Jodhpur

Publications: 28

Tieniu Tan

Tieniu Tan

Chinese Academy of Sciences

Publications: 27

Yasushi Yagi

Yasushi Yagi

Osaka University

Publications: 27

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