Da Teng

2.2k citations
75 papers · 1.6k · 1 hit paper · h-index 18

Impact in

Papers in

Da Teng

71 papers receiving 1.5k citations

Da Teng's Hit Papers

Phase recovery and holographic image reconstruction using deep learning in neural networks 2017 · 703 citations
7030+3+6Years since publication200400600

Peers

Da Teng
Comparison fields: 5 of 106
  • Acoustics and Ultrasonics 70
  • Media Technology 249
  • Atomic and Molecular Physics, and Optics 710
  • Radiation 188
  • Biophysics 112
Replace Rakesh Kumar Singh with:
Rakesh Kumar Singh India
Lingfeng Yu China
Jinho Kim South Korea
Xiangzhao Wang China
R. S. Sirohi India
W. M. Duncan United States
Rihong Zhu China
Jincheng Ni China
Lifa Hu China
Shuqin Lou China
Da Teng relative to Rakesh Kumar Singh India Rakesh Kumar Singh's profile →
Citations per field
00.5×3.4×
Rakesh Kumar Singh · 1×
Citations per year

Countries citing papers authored by Da Teng

Since Specialization
Citations

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

Fields of papers citing papers by Da Teng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Da Teng, 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 Da Teng Line = papers co-authored together Da Teng links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 75 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Phase recovery and holographic image reconstruction using deep learning in neural networks
Hit paper breakdown →
2017703
2 2017158
3 201951
4 199346
5 199445
6 202043
7 202036
8 202034
9 202132
10 201932
11 202132
12 201730
13 199327
14 201524
15 202022
16 202419
17 201719
18 202218
19 201916
20 201416

About Da Teng

Da Teng is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering, Atomic and Molecular Physics, and Optics, Materials Chemistry and Artificial Intelligence, having authored 75 papers that have together received 1.6k indexed citations. Recurring topics across this work include Photonic and Optical Devices (26 papers), Plasmonic and Surface Plasmon Research (24 papers), Photonic Crystals and Applications (14 papers), Graphene research and applications (10 papers), Catalytic Processes in Materials Science (10 papers), Semiconductor Quantum Structures and Devices (7 papers), Semiconductor Lasers and Optical Devices (5 papers) and Privacy-Preserving Technologies in Data (4 papers). The work is most often cited by research in Acoustics and Ultrasonics (70 citations), Media Technology (249 citations), Atomic and Molecular Physics, and Optics (710 citations), Radiation (188 citations) and Biophysics (112 citations). Da Teng has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Yair Rivenson, Aydogan Özcan, Yibo Zhang, Harun Günaydın, Kai Wang, Runlin Han, Shouhai Zhang, Yu‐Hwa Lo, Weiguang Chen and Zhe Li. Their work appears in journals such as Nanomaterials, Plasmonics, Optics Express, Applied Physics Letters and Molecular Physics.

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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