Anna Zhu
Impact in
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- Handwritten Text Recognition Techniques
- Image Retrieval and Classification Techniques
- Generative Adversarial Networks and Image Synthesis
- Health top 10%
Papers in
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- Gender, Labor, and Family Dynamics 13
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- Handwritten Text Recognition Techniques 19
- Image Retrieval and Classification Techniques 11
- Image Processing and 3D Reconstruction 9
- Generative Adversarial Networks and Image Synthesis 6
- Co-authors
- Deborah A. Cobb‐ClarkNicolás SalamancaSeiichi UchidaSimon FeenyTrong‐Anh TrinhJoel C. BornsteinCain PolidanoAgne Suziedelyte
In The Last Decade
Anna Zhu
72 papers receiving 670 citations
Peers
Comparison fields: 5 of 118
- Computer Vision and Pattern Recognition 169
- Health 54
- Gender Studies 60
- Media Technology 48
- Pollution 60
Countries citing papers authored by Anna Zhu
This map shows the geographic impact of Anna Zhu'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 Anna Zhu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anna Zhu more than expected).
Fields of papers citing papers by Anna Zhu
This network shows the impact of papers produced by Anna Zhu. 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 Anna Zhu. The network helps show where Anna Zhu may publish in the future.
Co-authors
The 25 scholars most cited alongside Anna Zhu, 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 | 2025 | 4 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 2 | |
| 5 | 2023 | 4 | |
| 6 | 2023 | 0 | |
| 7 | 2023 | 4 | |
| 8 | 2022 | 3 | |
| 9 | 2022 | 3 | |
| 10 | 2022 | 31 | |
| 11 | 2022 | 4 | |
| 12 | 2021 | 1 | |
| 13 | 2020 | 8 | |
| 14 | 2019 | 28 | |
| 15 | 2018 | 9 | |
| 16 | 2017 | 86 | |
| 17 | 2014 | 4 | |
| 18 | mage fusion based on region contrast in nonsubsampled Contourlet transform domain | 2010 | 0 |
| 19 | Comparing Disadvantage and Well-Being in Australian Families | 2009 | 6 |
| 20 | The Effect of Maternal Employment on the Likelihood of a Child Being Overweight (Discussion Paper: 2007/17) | 2009 | 3 |
About Anna Zhu
Anna Zhu is a scholar working on Gender Studies, Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Health and Demography, having authored 76 papers that have together received 700 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (19 papers), Gender, Labor, and Family Dynamics (13 papers), Image Retrieval and Classification Techniques (11 papers), Image Processing and 3D Reconstruction (9 papers), Family Dynamics and Relationships (8 papers), Generative Adversarial Networks and Image Synthesis (6 papers), Intergenerational and Educational Inequality Studies (6 papers) and Health disparities and outcomes (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (169 citations), Health (54 citations), Gender Studies (60 citations), Media Technology (48 citations) and Pollution (60 citations). Anna Zhu has collaborated with scholars based in Australia, China and Germany. Frequent co-authors include Deborah A. Cobb‐Clark, Nicolás Salamanca, Seiichi Uchida, Simon Feeny, Trong‐Anh Trinh, Joel C. Bornstein, Cain Polidano, Agne Suziedelyte, Brian Kenji Iwana and Silvia Mendolia. Their work appears in journals such as Journal of Population Economics, Journal of Economic Behavior & Organization, BMJ Open, Pattern Recognition and International Journal on Document Analysis and Recognition (IJDAR).
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.