Daniel Bankman

676 citations
16 papers · 449 · h-index 10

Impact in

Papers in

Daniel Bankman

16 papers receiving 439 citations

Peers

Daniel Bankman
Comparison fields: 5 of 55
  • Electrical and Electronic Engineering 367
  • Computer Vision and Pattern Recognition 105
  • Hardware and Architecture 34
  • Artificial Intelligence 121
  • Cellular and Molecular Neuroscience 40
Replace Daisuke Miyashita with:
Daisuke Miyashita Japan
Yukun Ding United States
Mohamed M. Sabry Aly Singapore
Taesik Na United States
Alfio Di Mauro Italy
Yuxiang Fu China
Yi Kang China
Avishek Biswas United States
Corey Lammie Australia
Daniel Bankman relative to Daisuke Miyashita Japan Daisuke Miyashita's profile →
Citations per field
00.5×1.5×
Daisuke Miyashita · 1×
Citations per year

Countries citing papers authored by Daniel Bankman

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Bankman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside Daniel Bankman, 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 Daniel Bankman Line = papers co-authored together Daniel Bankman links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 2018135
2 2018116
3 201539
4 201635
5 201834
6 201823
7 201915
8 201512
9 20199
10 20189
11 20198
12 20084
13 20184
14 20184
15 20071
16 20061

About Daniel Bankman

Daniel Bankman is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Biomedical Engineering, Aerospace Engineering and Artificial Intelligence, having authored 16 papers that have together received 449 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (7 papers), Advanced Neural Network Applications (5 papers), Analog and Mixed-Signal Circuit Design (5 papers), Ferroelectric and Negative Capacitance Devices (4 papers), CCD and CMOS Imaging Sensors (4 papers), Infrared Target Detection Methodologies (3 papers), Advancements in Semiconductor Devices and Circuit Design (3 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Electrical and Electronic Engineering (367 citations), Computer Vision and Pattern Recognition (105 citations), Hardware and Architecture (34 citations), Artificial Intelligence (121 citations) and Cellular and Molecular Neuroscience (40 citations). Daniel Bankman has collaborated with scholars based in United States and Belgium. Frequent co-authors include Boris Murmann, Bert Moons, Marian Verhelst, Lita Yang, Daisuke Miyashita, Andrew Yu, Jakob W. Messner, H.‐S. Philip Wong, Gage Hills and Subhasish Mitra. Their work appears in journals such as IEEE Solid-State Circuits Magazine, Optical Engineering, Electronics Letters, IEEE Journal of Solid-State Circuits and IEEE Conference Proceedings.

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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