Lei Ge

409 total citations
14 papers, 339 citations indexed

About

Lei Ge is a scholar working on Aquatic Science, Artificial Intelligence and Neurology. According to data from OpenAlex, Lei Ge has authored 14 papers receiving a total of 339 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Aquatic Science, 4 papers in Artificial Intelligence and 3 papers in Neurology. Recurrent topics in Lei Ge's work include Seaweed-derived Bioactive Compounds (4 papers), Echinoderm biology and ecology (4 papers) and Machine Learning and ELM (3 papers). Lei Ge is often cited by papers focused on Seaweed-derived Bioactive Compounds (4 papers), Echinoderm biology and ecology (4 papers) and Machine Learning and ELM (3 papers). Lei Ge collaborates with scholars based in China, Japan and United States. Lei Ge's co-authors include Long Yu, Xiaoqi Xu, Yaoguang Chang, Changhu Xue, Yanchao Wang, Guanchen Liu, Cuiyu Zhang, Jack Yang, Hong Lin and Zhenxing Li and has published in prestigious journals such as Food Chemistry, IEEE Access and Optics Communications.

In The Last Decade

Lei Ge

12 papers receiving 333 citations

Peers

Lei Ge
Min Ju Kim South Korea
Xinru Qi China
Stina Frosch Denmark
Lei Ge
Citations per year, relative to Lei Ge Lei Ge (= 1×) peers Luyao Tang

Countries citing papers authored by Lei Ge

Since Specialization
Citations

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

Fields of papers citing papers by Lei Ge

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lei Ge

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

All Works

14 of 14 papers shown
1.
Liang, Tao, et al.. (2024). An Energy-Saving Scheme to Reduce Throttling Losses in Hydraulic Excavators Based on Electro-Hydraulic Energy Storage. IEEE Access. 12. 125043–125056. 2 indexed citations
2.
Xie, Yun, Quanzhong Liu, Li Li, et al.. (2024). DaxibotulinumtoxinA for injection to treat moderate or severe glabellar lines: A randomized, multicenter, Phase III, double-blind, placebo-controlled trial in China. Journal of Plastic Reconstructive & Aesthetic Surgery. 99. 67–75. 1 indexed citations
4.
Ge, Lei. (2018). Generalization of LOD2 buildings with different roof structures. Journal of Spatial Science. 64(2). 319–340. 4 indexed citations
5.
Qiang, Yan, et al.. (2018). Automatic diagnosis of pulmonary nodules using a hierarchical extreme learning machine model. International Journal of Bio-Inspired Computation. 11(3). 192–192.
6.
Qiang, Yan, et al.. (2018). Automatic diagnosis of pulmonary nodules using a hierarchical extreme learning machine model. International Journal of Bio-Inspired Computation. 11(3). 192–192. 2 indexed citations
7.
Sang, Xinzhu, Shujun Xing, Xunbo Yu, et al.. (2017). High-efficient rendering of the multi-view image for the three-dimensional display based on the backward ray-tracing technique. Optics Communications. 405. 306–311. 14 indexed citations
8.
Qiang, Yan, Lei Ge, Xin Zhao, Xiaolong Zhang, & Xiaoxian Tang. (2017). Pulmonary nodule diagnosis using dual‐modal supervised autoencoder based on extreme learning machine. Expert Systems. 34(6). 12 indexed citations
9.
Ge, Lei, et al.. (2017). Development and application of a tyrosinase-based time-temperature indicator (TTI) for determining the quality of turbot sashimi. Journal of Ocean University of China. 16(5). 847–854. 15 indexed citations
10.
Yu, Long, Changhu Xue, Yaoguang Chang, et al.. (2015). Structure and rheological characteristics of fucoidan from sea cucumber Apostichopus japonicus. Food Chemistry. 180. 71–76. 63 indexed citations
11.
Yu, Long, Changhu Xue, Yaoguang Chang, et al.. (2013). Structure elucidation of fucoidan composed of a novel tetrafucose repeating unit from sea cucumber Thelenota ananas. Food Chemistry. 146. 113–119. 78 indexed citations
12.
Yu, Long, Lei Ge, Changhu Xue, et al.. (2013). Structural study of fucoidan from sea cucumber Acaudina molpadioides: A fucoidan containing novel tetrafucose repeating unit. Food Chemistry. 142. 197–200. 75 indexed citations
13.
Yu, Long, Xiaoqi Xu, Changhu Xue, et al.. (2013). Enzymatic preparation and structural determination of oligosaccharides derived from sea cucumber (Acaudina molpadioides) fucoidan. Food Chemistry. 139(1-4). 702–709. 57 indexed citations
14.
Li, Guozheng, Mingyu You, Lei Ge, Jack Yang, & Mary Qu Yang. (2010). Feature selection for semi-supervised multi-label learning with application to gene function analysis. 354–357. 16 indexed citations

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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