Alexander Graves
Impact in
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- Handwritten Text Recognition Techniques
- Image Processing and 3D Reconstruction
- Image Retrieval and Classification Techniques
- Artificial Intelligence top 2%
- Natural Language Processing Techniques
- Topic Modeling
Papers in
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- Ovarian cancer diagnosis and treatment 2
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- Appendicitis Diagnosis and Management 2
- Co-authors
- Jürgen SchmidhuberHorst BunkeS. George FernandezMarcus LiwickiRoman BertolamiRémi MunosMohammad Gheshlaghi AzarShane Legg
- Journals
- Annals of Surgical Oncology (2 papers)The Journal of Organic Chemistry (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Journal of Surgical Case Reports (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesSwitzerlandAustralia
In The Last Decade
Alexander Graves
8 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 143
- Computer Vision and Pattern Recognition 806
- Artificial Intelligence 801
- Human-Computer Interaction 116
- Signal Processing 215
- Media Technology 174
Countries citing papers authored by Alexander Graves
This map shows the geographic impact of Alexander Graves'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 Alexander Graves with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander Graves more than expected).
Fields of papers citing papers by Alexander Graves
This network shows the impact of papers produced by Alexander Graves. 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 Alexander Graves. The network helps show where Alexander Graves may publish in the future.
Co-authors
The 24 scholars most cited alongside Alexander Graves, 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 | 2024 | 3 | |
| 2 | 2024 | 1 | |
| 3 | 2020 | 5 | |
| 4 | 2019 | 0 | |
| 5 | Noisy Networks For Exploration | 2018 | 115 |
| 6 | 2016 | 3 | |
| 7 | 2016 | 23 | |
| 8 | A Novel Connectionist System for Unconstrained Handwriting Recognition Hit paper breakdown → | 2009 | 1312 |
| 9 | 2006 | 341 |
About Alexander Graves
Alexander Graves is a scholar working on Reproductive Medicine, Emergency Medicine, Human-Computer Interaction, Hardware and Architecture and Rheumatology, having authored 9 papers that have together received 1.8k indexed citations. Recurring topics across this work include Intraperitoneal and Appendiceal Malignancies (2 papers), Ovarian cancer diagnosis and treatment (2 papers), Appendicitis Diagnosis and Management (2 papers), Sarcoma Diagnosis and Treatment (1 paper), Asymmetric Synthesis and Catalysis (1 paper), Catalytic C–H Functionalization Methods (1 paper), Handwritten Text Recognition Techniques (1 paper) and Music and Audio Processing (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (806 citations), Artificial Intelligence (801 citations), Human-Computer Interaction (116 citations), Signal Processing (215 citations) and Media Technology (174 citations). Alexander Graves has collaborated with scholars based in United States, Switzerland and Australia. Frequent co-authors include Jürgen Schmidhuber, Horst Bunke, S. George Fernandez, Marcus Liwicki, Roman Bertolami, Rémi Munos, Mohammad Gheshlaghi Azar, Shane Legg, Bilal Piot and Jacob Menick. Their work appears in journals such as Annals of Surgical Oncology, The Journal of Organic Chemistry, IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Surgical Case Reports and arXiv (Cornell University).
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.