Samuel Cheng

3.4k citations
163 papers · 2.3k · 1 hit paper · h-index 26

Impact in

Papers in

Samuel Cheng

151 papers receiving 2.2k citations

Samuel Cheng's Hit Papers

A Survey on Deep Reinforcement Learning Algorithms for Robotic Manipulation 2023 · 99 citations
990+1+2Years since publication255075

Peers

Samuel Cheng
Comparison fields: 5 of 134
  • Computer Vision and Pattern Recognition 663
  • Computer Networks and Communications 511
  • Signal Processing 201
  • Health Informatics 23
  • Artificial Intelligence 527
Replace Jingmin Xin with:
Jingmin Xin China
Carlos Mosquera Spain
Xiaodong Yang China
Soumya Ranjan Nayak India
Tamer Khattab Qatar
Vijay Vasudevan United States
Ngan Le United States
Bin Sheng China
Andreas Weber⋆ Germany
Po-Yao Huang United States
Samuel Cheng relative to Jingmin Xin China Jingmin Xin's profile →
Citations per field
00.5×3.2×
Jingmin Xin · 1×
Citations per year

Countries citing papers authored by Samuel Cheng

Since Specialization
Citations

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

Fields of papers citing papers by Samuel Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Samuel Cheng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Samuel Cheng Line = papers co-authored together Samuel Cheng links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 163 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021122
2 2003103
3
A Survey on Deep Reinforcement Learning Algorithms for Robotic Manipulation
Hit paper breakdown →
202399
4 201783
5 199979
6 200878
7 201257
8 200557
9 201555
10 201355
11 200653
12 201652
13 200142
14 200439
15 201739
16 201939
17 200936
18 202035
19 200433
20 201433

About Samuel Cheng

Samuel Cheng is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Computer Networks and Communications, Artificial Intelligence and Signal Processing, having authored 163 papers that have together received 2.3k indexed citations. Recurring topics across this work include Wireless Communication Security Techniques (40 papers), Error Correcting Code Techniques (28 papers), Advanced Wireless Communication Techniques (15 papers), Image and Signal Denoising Methods (13 papers), Advanced Image and Video Retrieval Techniques (12 papers), Advanced Data Compression Techniques (12 papers), Advanced Image Processing Techniques (12 papers) and Sparse and Compressive Sensing Techniques (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (663 citations), Computer Networks and Communications (511 citations), Signal Processing (201 citations), Health Informatics (23 citations) and Artificial Intelligence (527 citations). Samuel Cheng has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Vladimir Stanković, Zixiang Xiong, Lina Stanković, Hong Liu, Bin Zheng, Shuang Wang, A.D. Liveris, Xiaoqian Jiang, Yuchen Qiu and Pramode K. Verma. Their work appears in journals such as IEEE Transactions on Communications, Emerging infectious diseases, IEEE Transactions on Signal Processing, Journal of Visual Communication and Image Representation and IEEE Transactions on Multimedia.

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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