Hugo L. Hammer
- Artificial Intelligence top 5%
- Oncology
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications top 10%
- Co-authors
- Michael A. RieglerAnis YazidiPål HalvorsenSteven A. HicksVajira ThambawitaThomas de LangeDag JohansenDebesh Jha
- Topics
- Machine Learning and Algorithms (11 papers)Data Stream Mining Techniques (10 papers)Reproductive Biology and Fertility (8 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
In The Last Decade
Hugo L. Hammer
91 papers receiving 886 citations
Hit Papers
Peers
Comparison fields: 5 of 133
- Artificial Intelligence 348
- Oncology 172
- Radiology, Nuclear Medicine and Imaging 164
- Computer Vision and Pattern Recognition 141
- Computer Networks and Communications 76
Countries citing papers authored by Hugo L. Hammer
This map shows the geographic impact of Hugo L. Hammer'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 Hugo L. Hammer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hugo L. Hammer more than expected).
Fields of papers citing papers by Hugo L. Hammer
This network shows the impact of papers produced by Hugo L. Hammer. 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 Hugo L. Hammer. The network helps show where Hugo L. Hammer may publish in the future.
Co-authorship network of co-authors of Hugo L. Hammer
This figure shows the co-authorship network connecting the top 25 collaborators of Hugo L. Hammer. A scholar is included among the top collaborators of Hugo L. Hammer based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hugo L. Hammer. Hugo L. Hammer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 4 | |
| 9 | 8 | |
| 10 | 9 | |
| 11 | 9 | |
| 12 | 5 | |
| 13 | Medico Multimedia Task at MediaEval 2019. | 5 |
| 14 | Predicting Sperm Motility and Morphology Using Deep Learning and Handcrafted Features. | 2 |
| 15 | The Medico-Task 2018: Disease Detection in the Gastrointestinal Tract Using Global Features and Deep Learning. | 1 |
| 16 | 4 | |
| 17 | 0 | |
| 18 | Does clicker use improve exam scores? a controlled randomized experiment in a bachelor-level course in software engineering | 6 |
| 19 | 9 | |
| 20 | 2 |
About Hugo L. Hammer
Hugo L. Hammer is a scholar working on Health Informatics, Artificial Intelligence and General Dentistry, having authored 99 papers that have together received 913 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (11 papers), Data Stream Mining Techniques (10 papers) and Reproductive Biology and Fertility (8 papers). The work is most often cited by research in Health Informatics (40 citations), Artificial Intelligence (348 citations) and Gastroenterology (57 citations). Hugo L. Hammer has collaborated with scholars based in Norway, Sweden and Canada. Frequent co-authors include Michael A. Riegler, Anis Yazidi, Pål Halvorsen, Steven A. Hicks, Vajira Thambawita, Thomas de Lange, Dag Johansen, Debesh Jha, Håkon Tjelmeland and Mathias Lux. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.
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.