An‐Chieh Cheng

783 citations
19 papers · 285 · h-index 12

Impact in

Papers in

An‐Chieh Cheng

19 papers receiving 283 citations

Peers

An‐Chieh Cheng
Comparison fields: 5 of 66
  • Computer Vision and Pattern Recognition 69
  • Computer Networks and Communications 58
  • Artificial Intelligence 50
  • Computer Science Applications 8
  • Atomic and Molecular Physics, and Optics 46
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Citations per field
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Citations per year

Countries citing papers authored by An‐Chieh Cheng

Since Specialization
Citations

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

Fields of papers citing papers by An‐Chieh Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

19 of 19 papers shown
#Work
1 201735
2 202031
3 202128
4 201727
5 202026
6 202023
7 202217
8
PPP-Net: Platform-aware Progressive Search for Pareto-optimal Neural Architectures.
201816
9 202416
10 202116
11
Mitigating Forgetting in Online Continual Learning via Instance-Aware Parameterization
202013
12 201713
13 20246
14 20245
15
Distributed analytics in fog computing platforms using tensorflow and kubernetes
20174
16 20253
17 20243
18 20242
19 20231

About An‐Chieh Cheng

An‐Chieh Cheng is a scholar working on Computer Vision and Pattern Recognition, Atomic and Molecular Physics, and Optics, Molecular Biology, Cellular and Molecular Neuroscience and Artificial Intelligence, having authored 19 papers that have together received 285 indexed citations. Recurring topics across this work include Photoreceptor and optogenetics research (4 papers), Orbital Angular Momentum in Optics (3 papers), Molecular spectroscopy and chirality (2 papers), Advanced Neural Network Applications (2 papers), Multimodal Machine Learning Applications (2 papers), IoT and Edge/Fog Computing (2 papers), Cloud Computing and Resource Management (2 papers) and Spectroscopy and Quantum Chemical Studies (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (69 citations), Computer Networks and Communications (58 citations), Artificial Intelligence (50 citations), Computer Science Applications (8 citations) and Atomic and Molecular Physics, and Optics (46 citations). An‐Chieh Cheng has collaborated with scholars based in Taiwan, Japan and United States. Frequent co-authors include Teruki Sugiyama, Hua-Jun Hong, Pei-Hsuan Tsai, Cheng-Hsin Hsu, Da-Cheng Juan, Min Sun, Keiji Sasaki, Hiroshi Masuhara, Hiromasa Niinomi and Wei Wei. Their work appears in journals such as The Journal of Physical Chemistry C, Cell Death and Disease, The Journal of Physical Chemistry Letters, The Journal of Chemical Physics and PLoS ONE.

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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