Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
KVASIR
2017381 citationsKonstantin Pogorelov, Kristin Ranheim Randel et al.Arrow@dit (Dublin Institute of Technology)profile →
HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy
2020261 citationsSteven A. Hicks, Sigrun Losada Eskeland et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Mathias Lux'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 Mathias Lux with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mathias Lux more than expected).
This network shows the impact of papers produced by Mathias Lux. 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 Mathias Lux. The network helps show where Mathias Lux may publish in the future.
Co-authorship network of co-authors of Mathias Lux
This figure shows the co-authorship network connecting the top 25 collaborators of Mathias Lux.
A scholar is included among the top collaborators of Mathias Lux 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 Mathias Lux. Mathias Lux is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Ninh, Van-Tu, Liting Zhou, Luca Piras, et al.. (2020). Organiser Team at ImageCLEFlifelog 2020: A Baseline Approach for Moment Retrieval and Athlete Performance Prediction using Lifelog Data. Duo Research Archive (University of Oslo).
2.
Ninh, Van-Tu, Liting Zhou, Luca Piras, et al.. (2020). Overview of ImageCLEF Lifelog 2020: Lifelog Moment Retrieval and Sport Performance Lifelog. Duo Research Archive (University of Oslo).3 indexed citations
3.
Hicks, Steven A., Pål Halvorsen, Trine B. Haugen, et al.. (2019). Medico Multimedia Task at MediaEval 2019.. MediaEval.5 indexed citations
4.
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
5.
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
6.
Steiner, Michael, Mathias Lux, & Pål Halvorsen. (2018). The 2018 Medico Multimedia Task Submission of Team NOAT Using Neural Network Features and Search-based Classification.. MediaEval.1 indexed citations
7.
Pogorelov, Konstantin, Michael A. Riegler, Pål Halvorsen, et al.. (2018). Medico multimedia task at MediaEval 2018. Bergen Open Research Archive (BORA) (University of Bergen). 2283. 1–4.3 indexed citations
8.
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
9.
Lux, Mathias, et al.. (2018). GameStory Task at MediaEval 2018.. MediaEval.2 indexed citations
10.
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
11.
Petscharnig, Stefan, Klaus Schöffmann, & Mathias Lux. (2017). An Inception-like CNN Architecture for GI Disease and Anatomical Landmark Classification.. MediaEval.16 indexed citations
12.
Pogorelov, Konstantin, Michael A. Riegler, Pål Halvorsen, et al.. (2017). A Comparison of Deep Learning with Global Features for Gastrointestinal Disease Detection.. Arrow@dit (Dublin Institute of Technology).4 indexed citations
13.
Leibetseder, Andreas & Mathias Lux. (2016). Gamifying Fitness or Fitnessifying Games: a Comparative Study.. International ACM SIGIR Conference on Research and Development in Information Retrieval. 37–44.1 indexed citations
14.
Chatzichristofis, Savvas A., Loukas Bampis, Oge Marques, Mathias Lux, & Yiannis S. Boutalis. (2014). Image Encryption Using the Recursive Attributes of the exclusive-OR Filter.. 9. 125–137.1 indexed citations
15.
Riegler, Michael A., et al.. (2013). Frame the Crowd: Global Visual Features Labeling boosted with Crowdsourcing Information. MediaEval.3 indexed citations
Strohmaier, Markus, Peter Prettenhofer, & Mathias Lux. (2008). Different degrees of explicitness in intentional artifacts: studying user goals in a large search query log. 26–35.5 indexed citations
20.
Tochtermann, Klaus, et al.. (2003). IMB-Ein XML-basiertes Retrievalframework für digitales Audio und Video.. 103–113.2 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.