Nanying Liang

10 papers receiving 1.9k citations

Hit Papers

A Fast and Accurate Online Sequential Learning Algorithm ...2006202620122019200650010001.5k

Peers

Nanying Liang
Comparison fields: 5 of 119
  • Artificial Intelligence 1.5k
  • Electrical and Electronic Engineering 569
  • Computer Vision and Pattern Recognition 300
  • Control and Systems Engineering 268
  • Cognitive Neuroscience 228
Replace Cheng‐Jian Lin with:
Cheng‐Jian Lin Taiwan
Xinzheng Xu China
Zhidong Deng China
Yuan Lan China
Guilherme A. Barreto Brazil
Mohammad Mehdi Ebadzadeh Iran
Yong-Ping Zhao China
Anurag Singh India
S. Maouche France
Wisnu Jatmiko Indonesia
Nanying Liang relative to Cheng‐Jian Lin Taiwan Cheng‐Jian Lin's profile →
Citations per field
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Cheng‐Jian Lin · 1×
Citations per year

Countries citing papers authored by Nanying Liang

Since Specialization
Citations

This map shows the geographic impact of Nanying Liang'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 Nanying Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nanying Liang more than expected).

Fields of papers citing papers by Nanying Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nanying Liang. 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 Nanying Liang. The network helps show where Nanying Liang may publish in the future.

Co-authorship network of co-authors of Nanying Liang

This figure shows the co-authorship network connecting the top 25 collaborators of Nanying Liang. A scholar is included among the top collaborators of Nanying Liang 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 Nanying Liang. Nanying Liang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
#WorkIndexed citations
1 1
2 10
3 13
4 27
5 59
6
Band-specific features improve Finger Flexion Prediction from ECoG
10
7
Averaging techniques for single-trial analysis of oddball event-related potentials
19
8
A Fast and Accurate Online Sequential Learning Algorithm for Feedforward Networksbreakdown →
1522
9 202
10 147

About Nanying Liang

Nanying Liang is a scholar working on Human-Computer Interaction, Geology and Cognitive Neuroscience, having authored 10 papers that have together received 2.0k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (4 papers), Machine Learning and ELM (4 papers) and Neural Networks and Applications (3 papers). The work is most often cited by research in Artificial Intelligence (1.5k citations), Computer Vision and Pattern Recognition (300 citations) and Cognitive Neuroscience (228 citations). Nanying Liang has collaborated with scholars based in Singapore, United Kingdom and Brazil. Frequent co-authors include Guang-Bin Huang, P. Saratchandran, N. Sundararajan, N. Sundararajan, Laurent Bougrain, Hai-Jun Rong, Xulei Yang, Steven C. H. Hoi, Zeng Zeng and Lihui Huang. Their work appears in journals such as Neurocomputing, Automation in Construction and Frontiers in Neuroscience.

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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