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.
Collecting complex activity datasets in highly rich networked sensor environments
2010524 citationsDaniel Roggen, Alberto Calatroni et al.Infoscience (Ecole Polytechnique Fédérale de Lausanne)profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of David Bannach'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 David Bannach with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Bannach more than expected).
This network shows the impact of papers produced by David Bannach. 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 David Bannach. The network helps show where David Bannach may publish in the future.
Co-authorship network of co-authors of David Bannach
This figure shows the co-authorship network connecting the top 25 collaborators of David Bannach.
A scholar is included among the top collaborators of David Bannach 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 David Bannach. David Bannach 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.
Bannach, David. (2015). Tools and Methods to Support Opportunistic Human Activity Recognition. Publication Server of Kaiserslautern University of Technology (Kaiserslautern University of Technology).4 indexed citations
Kunze, Kai & David Bannach. (2012). Towards dynamically configurable context recognition systems. National Conference on Artificial Intelligence. 60–64.1 indexed citations
Bannach, David & Paul Lukowicz. (2011). Integrated Tool Chain for Recording, Handling, and Utilizing Large, Multimodal Context Data Sets for Context Recognition Systems..2 indexed citations
8.
Bannach, David, Bernhard Sick, & Paul Lukowicz. (2011). Automatic Adaptation of Mobile Activity Recognition Systems to New Sensors.6 indexed citations
Lukowicz, Paul, Gerald Pirkl, David Bannach, et al.. (2010). Recording a Complex, Multi Modal Activity Data Set for Context Recognition. 1–166.20 indexed citations
11.
Chavarriaga, Ricardo, Hesam Sagha, Hamidreza Bayati, et al.. (2010). Robust activity recognition for assistive technologies: Benchmarking machine learning techniques. Infoscience (Ecole Polytechnique Fédérale de Lausanne).3 indexed citations
Lukowicz, Paul, Gerald Pirkl, David Bannach, et al.. (2010). Recording a complex, multi modal activity data set for context recogntion. Infoscience (Ecole Polytechnique Fédérale de Lausanne).23 indexed citations
14.
Roggen, Daniel, Alberto Calatroni, Mirco Rossi, et al.. (2010). Collecting complex activity datasets in highly rich networked sensor environments. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 233–240.524 indexed citations breakdown →
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.