Qixin Sha

843 citations
27 papers · 599 indexed · 1 hit paper · h-index 11
Topics
Underwater Vehicles and Communication Systems (21 papers)Machine Learning and ELM (8 papers)Adaptive Control of Nonlinear Systems (7 papers)

In The Last Decade

Qixin Sha

26 papers receiving 585 citations

Hit Papers

Path planning and obstacle avoidance for AUV: A review2021202620222024202150100150200

Peers

Qixin Sha
Comparison fields: 5 of 56
  • Ocean Engineering 347
  • Computer Vision and Pattern Recognition 273
  • Control and Systems Engineering 170
  • Artificial Intelligence 137
  • Aerospace Engineering 137
Replace Yue Shen with:
Yue Shen China
Yushan Sun China
Pedro Patrón United Kingdom
Somaiyeh MahmoudZadeh Australia
Yulei Liao China
Qinghua Luo China
Andrew Lammas Australia
Bruno Jouvencel France
Jialing Tang China
Abdelkrim Nemra Algeria
Qixin Sha relative to Yue Shen China Yue Shen's profile →
Citations per field
00.5×1.5×
Yue Shen · 1×
Citations per year

Countries citing papers authored by Qixin Sha

Since Specialization
Citations

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

Fields of papers citing papers by Qixin Sha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qixin Sha

This figure shows the co-authorship network connecting the top 25 collaborators of Qixin Sha. A scholar is included among the top collaborators of Qixin Sha 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 Qixin Sha. Qixin Sha 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 7
2 5
3 14
4 30
5 28
6 6
7 27
8 86
9 10
10 37
11
Controller design of an autonomous underwater vehicle using ELM-based sliding mode control
0
12 8
13 2
14 7
15 1
16 38
17 6
18 1
19 2
20 1

About Qixin Sha

Qixin Sha is a scholar working on Ocean Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 27 papers that have together received 599 indexed citations. Recurring topics across this work include Underwater Vehicles and Communication Systems (21 papers), Machine Learning and ELM (8 papers) and Adaptive Control of Nonlinear Systems (7 papers). The work is most often cited by research in Ocean Engineering (347 citations), Computer Vision and Pattern Recognition (273 citations) and Control and Systems Engineering (170 citations). Qixin Sha has collaborated with scholars based in China, United States and Finland. Frequent co-authors include Guangliang Li, Bo He, Bo He, Yue Shen, Tianhong Yan, Dianrui Wang, Jia Guo, Junhe Wan, Yan Song and Rui Nian. Their work appears in journals such as IEEE Access, Neurocomputing and Ocean Engineering.

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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