Li-Ming Zhao

42 papers receiving 1.6k citations

Hit Papers

Deeply-Learned Part-Aligned Representations for Person Re...201620262019202220172016100200300400500

Peers

Li-Ming Zhao
Comparison fields: 5 of 109
  • Computer Vision and Pattern Recognition 1.1k
  • Biomedical Engineering 281
  • Cognitive Neuroscience 261
  • Human-Computer Interaction 172
  • Experimental and Cognitive Psychology 171
Replace Tim K. Marks with:
Tim K. Marks United States
Jannik Fritsch Germany
Cristóbal Curio Germany
Ravish Mehra United States
Simone Frintrop Germany
Yusuke Sugano Japan
Jing Xiao China
Eui Chul Lee South Korea
Menglong Zhu United States
Li-Ming Zhao relative to Tim K. Marks United States Tim K. Marks's profile →
Citations per field
00.5×1.5×1.9×
Tim K. Marks · 1×
Citations per year

Countries citing papers authored by Li-Ming Zhao

Since Specialization
Citations

This map shows the geographic impact of Li-Ming Zhao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Li-Ming Zhao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Li-Ming Zhao more than expected).

Fields of papers citing papers by Li-Ming Zhao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Li-Ming Zhao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Li-Ming Zhao. The network helps show where Li-Ming Zhao may publish in the future.

Co-authorship network of co-authors of Li-Ming Zhao

This figure shows the co-authorship network connecting the top 25 collaborators of Li-Ming Zhao. A scholar is included among the top collaborators of Li-Ming Zhao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Li-Ming Zhao. Li-Ming Zhao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 3
3 4
4 97
5 4
6
Deeply-Learned Part-Aligned Representations for Person Re-identificationbreakdown →
553
7 25
8 18
9
On the Connection of Deep Fusion to Ensembling.
23
10
Effects of irrigation methods and rice planting densities on yield and photosynthetic characteristics of matter production in cold area.
11
11
Relationship between Grain Composition and Quality of Rice
1
12
Current Research Advances on Plant Hormones and Regulation of Plant Development by Plant Hormones in Rice
1
13 40
14 7
15
Fuzzy Neural Network Controller of Inverted Pendulum with Reinforcement Learn ing Rule
0
16 1
17 28
18 8
19
Fossil Plants from Xingyuan Formation, Pingzhuang Chifeng, Nei Monggol
1
20
Studies on the Pleozoic Seed---Genus Callospermarion
4

About Li-Ming Zhao

Li-Ming Zhao is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Cognitive Neuroscience, having authored 46 papers that have together received 1.6k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (11 papers), Gaze Tracking and Assistive Technology (8 papers) and Emotion and Mood Recognition (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Human-Computer Interaction (172 citations) and Cognitive Neuroscience (261 citations). Li-Ming Zhao has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Xi Li, Jingdong Wang, Yueting Zhuang, Bao‐Liang Lu, Fei Wu, Ming–Hsuan Yang, Lina Wei, Haibin Ling, Jane Huffman Hayes and Erdan Gu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Neurocomputing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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