Countries citing papers authored by Michael Riegler
Since
Specialization
Citations
This map shows the geographic impact of Michael Riegler'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 Michael Riegler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Riegler more than expected).
This network shows the impact of papers produced by Michael Riegler. 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 Michael Riegler. The network helps show where Michael Riegler may publish in the future.
Co-authorship network of co-authors of Michael Riegler
This figure shows the co-authorship network connecting the top 25 collaborators of Michael Riegler.
A scholar is included among the top collaborators of Michael Riegler 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 Michael Riegler. Michael Riegler is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Riegler, Michael, Johannes Sametinger, & Jerzy W. Rozenblit. (2022). Context-Aware Security Modes For Medical Devices. University Library Linz repository (Johannes Kepler Universitat Linz).2 indexed citations
10.
Dang‐Nguyen, Duc‐Tien, Luca Piras, Michael Riegler, et al.. (2019). Overview of ImageCLEFlifelog 2019: Solve My Life Puzzle and Lifelog Moment Retrieval.. Arrow@dit (Dublin Institute of Technology).12 indexed citations
11.
Hicks, Steven A., Pål Halvorsen, Trine B. Haugen, et al.. (2019). Predicting Sperm Motility and Morphology Using Deep Learning and Handcrafted Features.. MediaEval.2 indexed citations
12.
Pogorelov, Konstantin, Kashif Ahmad, Michael Riegler, et al.. (2018). Deep Learning Approaches for Flood Classification and Flood Aftermath Detection.. Institutional Research Information System (Università degli Studi di Trento).9 indexed citations
13.
Dang‐Nguyen, Duc‐Tien, Luca Piras, Michael Riegler, et al.. (2018). Overview of ImageCLEFlifelog 2018: daily living understanding and lifelog moment retrieval. Arrow@dit (Dublin Institute of Technology). 2125.19 indexed citations
14.
Zhou, Liting, Luca Piras, Michael Riegler, et al.. (2018). An Interactive Lifelog Retrieval System for Activities of Daily Living Understanding.. UNICA IRIS Institutional Research Information System (University of Cagliari).2 indexed citations
15.
Halvorsen, Pål, et al.. (2018). Automatic Hyperparameter Optimization in Keras for the MediaEval 2018 Medico Multimedia Task.. MediaEval.6 indexed citations
16.
Pogorelov, Konstantin, et al.. (2018). Transfer Learning with Prioritized Classification and Training Dataset Equalization for Medical Objects Detection.. MediaEval.3 indexed citations
17.
Zhou, Liting, Luca Piras, Michael Riegler, et al.. (2017). Organizer team at ImageCLEFlifelog 2017: baseline approaches for lifelog retrieval and summarization. Arrow@dit (Dublin Institute of Technology). 1866.9 indexed citations
18.
Ahmad, Kashif, Konstantin Pogorelov, Michael Riegler, Nicola Conci, & Pål Halvorsen. (2017). CNN and GAN Based Satellite and Social Media Data Fusion for Disaster Detection.. Institutional Research Information System (Università degli Studi di Trento).27 indexed citations
19.
Dang‐Nguyen, Duc‐Tien, Luca Piras, Michael Riegler, et al.. (2017). Overview of ImageCLEFlifelog 2017: Lifelog Retrieval and Summarization.. Arrow@dit (Dublin Institute of Technology).15 indexed citations
20.
Boididou, Christina, et al.. (2015). Verifying Multimedia Use at MediaEval 2015. MediaEval.106 indexed citations
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.