Jana Machajdik
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 10%
- Cognitive Neuroscience top 10%
- Experimental and Cognitive Psychology top 10%
- Social Psychology top 10%
- Co-authors
- Allan HanburyMartin KampelSebastian ZambaniniRobert SablatnigJulian StöttingerRoberto ValentiDietmar BrucknerPhotchara Ratsamee
- Topics
- Video Surveillance and Tracking Methods (3 papers)Psychiatry, Mental Health, Neuroscience (3 papers)Context-Aware Activity Recognition Systems (3 papers)
- Journals
- Machine Vision and ApplicationsUvA-DARE (University of Amsterdam)
- Partner nations
- AustriaUnited StatesSingapore
In The Last Decade
Jana Machajdik
9 papers receiving 590 citations
Hit Papers
Peers
Comparison fields: 5 of 70
- Computer Vision and Pattern Recognition 424
- Artificial Intelligence 181
- Cognitive Neuroscience 116
- Experimental and Cognitive Psychology 109
- Social Psychology 100
Countries citing papers authored by Jana Machajdik
This map shows the geographic impact of Jana Machajdik'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 Jana Machajdik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jana Machajdik more than expected).
Fields of papers citing papers by Jana Machajdik
This network shows the impact of papers produced by Jana Machajdik. 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 Jana Machajdik. The network helps show where Jana Machajdik may publish in the future.
Co-authorship network of co-authors of Jana Machajdik
This figure shows the co-authorship network connecting the top 25 collaborators of Jana Machajdik. A scholar is included among the top collaborators of Jana Machajdik 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 Jana Machajdik. Jana Machajdik is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | A Keyframe Selection of Lifelog Image Sequences | 5 |
| 2 | 2 | |
| 3 | 1 | |
| 4 | Affective computing for wearable diary and lifelogging systems: An overview | 10 |
| 5 | 5 | |
| 6 | 1 | |
| 7 | 12 | |
| 8 | Affective image classification using features inspired by psychology and art theorybreakdown → | 565 |
| 9 | Fusion of Data from Multiple Cameras for Fall Detection | 5 |
About Jana Machajdik
Jana Machajdik is a scholar working on Computer Vision and Pattern Recognition, Social Psychology and Cognitive Neuroscience, having authored 9 papers that have together received 606 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (3 papers), Psychiatry, Mental Health, Neuroscience (3 papers) and Context-Aware Activity Recognition Systems (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (424 citations), Experimental and Cognitive Psychology (109 citations) and Urban Studies (40 citations). Jana Machajdik has collaborated with scholars based in Austria, United States and Singapore. Frequent co-authors include Allan Hanbury, Martin Kampel, Sebastian Zambanini, Robert Sablatnig, Julian Stöttinger, Roberto Valenti, Dietmar Bruckner, Photchara Ratsamee, Kenichi Ohara and Rosemarie Velik. Their work appears in journals such as Machine Vision and Applications and UvA-DARE (University of Amsterdam).
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.