D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Materials Science D-index 48 Citations 7,294 313 World Ranking 6146 National Ranking 1564

Overview

What is he best known for?

The fields of study he is best known for:

  • Gene
  • Quantum mechanics
  • Internal medicine

Jun Liu mainly investigates Chemical engineering, Artificial intelligence, Photochemistry, Nanotechnology and Polymer. His biological study spans a wide range of topics, including Inorganic chemistry, Organic chemistry, Anode and Doping. His Artificial intelligence research includes themes of Machine learning and Pattern recognition.

His Photochemistry research incorporates themes from Organic semiconductor and Electroluminescence, Polyfluorene. Jun Liu interconnects Electrode and Lithium in the investigation of issues within Nanotechnology. Jun Liu combines subjects such as HOMO/LUMO and Electron acceptor with his study of Polymer.

His most cited work include:

  • Chest CT for Typical Coronavirus Disease 2019 (COVID-19) Pneumonia: Relationship to Negative RT-PCR Testing. (948 citations)
  • NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis (774 citations)
  • Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition (679 citations)

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

Jun Liu mostly deals with Chemical engineering, Artificial intelligence, Polymer, Optoelectronics and Internal medicine. Chemical engineering is frequently linked to Nanotechnology in his study. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning, Computer vision and Pattern recognition.

His work deals with themes such as Photochemistry, Acceptor and HOMO/LUMO, which intersect with Polymer. Much of his study explores Internal medicine relationship to Endocrinology. His Conjugated system research includes elements of Side chain and Polymer chemistry.

He most often published in these fields:

  • Chemical engineering (13.72%)
  • Artificial intelligence (10.29%)
  • Polymer (13.59%)

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

  • Polymer (13.59%)
  • Artificial intelligence (10.29%)
  • Chemical engineering (13.72%)

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

His main research concerns Polymer, Artificial intelligence, Chemical engineering, Optoelectronics and Conjugated system. His Polymer research incorporates elements of Acceptor, HOMO/LUMO and Energy conversion efficiency. Jun Liu has researched Artificial intelligence in several fields, including Machine learning and Pattern recognition.

His work carried out in the field of Pattern recognition brings together such families of science as Noise and Feature. Many of his studies on Chemical engineering apply to Work as well. His Conjugated system research is multidisciplinary, relying on both Thermoelectric effect and Doping.

Between 2019 and 2021, his most popular works were:

  • Chest CT for Typical Coronavirus Disease 2019 (COVID-19) Pneumonia: Relationship to Negative RT-PCR Testing. (948 citations)
  • Relation Between Chest CT Findings and Clinical Conditions of Coronavirus Disease (COVID-19) Pneumonia: A Multicenter Study. (489 citations)
  • NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding (159 citations)

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

  • Gene
  • Quantum mechanics
  • Internal medicine

Jun Liu mostly deals with Chemical engineering, Artificial intelligence, Polymer, Radiology and Pattern recognition. His research integrates issues of Photocatalysis, Catalysis, Doping and Surface engineering in his study of Chemical engineering. His studies in Artificial intelligence integrate themes in fields like Machine learning and Computer vision.

As a member of one scientific family, Jun Liu mostly works in the field of Machine learning, focusing on RGB color model and, on occasion, Feature extraction. The study incorporates disciplines such as Optoelectronics and Acceptor in addition to Polymer. His studies deal with areas such as Noise and Feature as well as Pattern recognition.

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

Chest CT for Typical Coronavirus Disease 2019 (COVID-19) Pneumonia: Relationship to Negative RT-PCR Testing.

Xingzhi Xie;Zheng Zhong;Wei Zhao;Chao Zheng.
Radiology (2020)

1468 Citations

NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis

Amir Shahroudy;Jun Liu;Tian-Tsong Ng;Gang Wang.
computer vision and pattern recognition (2016)

879 Citations

Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition

Jun Liu;Amir Shahroudy;Dong Xu;Gang Wang.
european conference on computer vision (2016)

834 Citations

Relation Between Chest CT Findings and Clinical Conditions of Coronavirus Disease (COVID-19) Pneumonia: A Multicenter Study.

Wei Zhao;Zheng Zhong;Xingzhi Xie;Qizhi Yu.
American Journal of Roentgenology (2020)

737 Citations

Tumor development is associated with decrease of TET gene expression and 5-methylcytosine hydroxylation

Yang H;Liu Y;Bai F;Zhang Jy.
Oncogene (2013)

519 Citations

Global Context-Aware Attention LSTM Networks for 3D Action Recognition

Jun Liu;Gang Wang;Ping Hu;Ling-Yu Duan.
computer vision and pattern recognition (2017)

361 Citations

Hydrothermally Stable Ordered Hexagonal Mesoporous Aluminosilicates Assembled from a Triblock Copolymer and Preformed Aluminosilicate Precursors in Strongly Acidic Media

Yu Han;Shuo Wu;Yinyong Sun;Dongsheng Li.
Chemistry of Materials (2002)

271 Citations

A Simple Method To Synthesize Nanowires

Yingjiu Zhang;Nanlin Wang;Shangpeng Gao;Rongrui He.
Chemistry of Materials (2002)

269 Citations

Synthesis of Mo2N nanolayer coated MoO2 hollow nanostructures as high-performance anode materials for lithium-ion batteries

Jun Liu;Shasha Tang;Yakun Lu;Gemei Cai.
Energy and Environmental Science (2013)

259 Citations

Skeleton-Based Human Action Recognition With Global Context-Aware Attention LSTM Networks

Jun Liu;Gang Wang;Ling-Yu Duan;Kamila Abdiyeva.
IEEE Transactions on Image Processing (2018)

241 Citations

Best Scientists Citing Jun Liu

Yong Cao

Yong Cao

South China University of Technology

Publications: 50

Wei Huang

Wei Huang

Nanjing Tech University

Publications: 42

Lixiang Wang

Lixiang Wang

Chinese Academy of Sciences

Publications: 37

Wanqing Li

Wanqing Li

University of Wollongong

Publications: 36

Fei Huang

Fei Huang

South China University of Technology

Publications: 27

Lei Ying

Lei Ying

South China University of Technology

Publications: 26

Buxing Han

Buxing Han

Chinese Academy of Sciences

Publications: 26

Weihong Tan

Weihong Tan

Hunan University

Publications: 25

He Yan

He Yan

Hong Kong University of Science and Technology

Publications: 25

Kai Dai

Kai Dai

Huaibei Normal University

Publications: 24

Yongfang Li

Yongfang Li

Soochow University

Publications: 24

Dinggang Shen

Dinggang Shen

ShanghaiTech University

Publications: 23

Junsong Yuan

Junsong Yuan

University at Buffalo, State University of New York

Publications: 21

Jie Min

Jie Min

Wuhan University

Publications: 21

Wenjun Zeng

Wenjun Zeng

Microsoft (United States)

Publications: 19

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

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