Ethan Goan
Impact in
- Analytical Chemistry top 5%
- Spectroscopy and Chemometric Analyses
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- Advanced Image and Video Retrieval Techniques
- Image Retrieval and Classification Techniques
- Multimodal Machine Learning Applications
Papers in
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- Domain Adaptation and Few-Shot Learning 1
- Neural Networks and Applications 1
- Wireless Signal Modulation Classification 1
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- Machine Fault Diagnosis Techniques 1
- Co-authors
- Clinton Fookes (4 shared papers)Daniel B. Ward (1 shared paper)Srimal Jayawardena (1 shared paper)Pavan Sikka (1 shared paper)Peyman Moghadam (1 shared paper)Emili Hernández (1 shared paper)Simon Denman (2 shared papers)Sridha Sridharan (1 shared paper)
- Journals
- Pattern Recognition (1 paper)Queensland's institutional digital repository (The University of Queensland) (1 paper)Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (1 paper)QUT ePrints (Queensland University of Technology) (1 paper)
- Partner nations
- Australia
In The Last Decade
Ethan Goan
6 papers receiving 296 citations
Peers
Comparison fields: 5 of 79
- Analytical Chemistry 76
- Computer Vision and Pattern Recognition 68
- Plant Science 105
- Media Technology 24
- Statistics, Probability and Uncertainty 18
Countries citing papers authored by Ethan Goan
This map shows the geographic impact of Ethan Goan'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 Ethan Goan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ethan Goan more than expected).
Fields of papers citing papers by Ethan Goan
This network shows the impact of papers produced by Ethan Goan. 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 Ethan Goan. The network helps show where Ethan Goan may publish in the future.
Co-authors
The 10 scholars most cited alongside Ethan Goan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 122 | |
| 2 | Bayesian neural networks: An introduction and survey | 2020 | 120 |
| 3 | 2022 | 46 | |
| 4 | 2016 | 17 | |
| 5 | 2023 | 6 | |
| 6 | 2024 | 3 |
About Ethan Goan
Ethan Goan is a scholar working on Artificial Intelligence, Control and Systems Engineering, Computer Vision and Pattern Recognition, Automotive Engineering and Ecology, having authored 6 papers that have together received 314 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (1 paper), Remote Sensing in Agriculture (1 paper), Autonomous Vehicle Technology and Safety (1 paper), Advanced SAR Imaging Techniques (1 paper), Neural Networks and Applications (1 paper), Optical Polarization and Ellipsometry (1 paper), Machine Fault Diagnosis Techniques (1 paper) and Wireless Signal Modulation Classification (1 paper). The work is most often cited by research in Analytical Chemistry (76 citations), Computer Vision and Pattern Recognition (68 citations), Plant Science (105 citations), Media Technology (24 citations) and Statistics, Probability and Uncertainty (18 citations). Ethan Goan has collaborated with scholars based in Australia. Frequent co-authors include Clinton Fookes, Daniel B. Ward, Srimal Jayawardena, Pavan Sikka, Peyman Moghadam, Emili Hernández, Simon Denman, Sridha Sridharan, Branislav Kusý and Reza Arablouei. Their work appears in journals such as Pattern Recognition, Queensland's institutional digital repository (The University of Queensland), Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE and QUT ePrints (Queensland University of Technology).
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.