Innar Liiv

26 papers receiving 227 citations

Peers

Innar Liiv
Comparison fields: 5 of 88
  • Computer Vision and Pattern Recognition 79
  • Public Administration 12
  • Signal Processing 35
  • Statistical and Nonlinear Physics 26
  • Artificial Intelligence 54
Replace Juhee Bae with:
Juhee Bae Sweden
Daniel Seebacher Germany
Emily Wall United States
María Teresa Signes Pont Spain
Eirini Ntoutsi Germany
John Wenskovitch United States
Tyng–Ruey Chuang Taiwan
Ruixun Zhang China
Hannah Kim United States
Innar Liiv relative to Juhee Bae Sweden Juhee Bae's profile →
Citations per field
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Citations per year

Countries citing papers authored by Innar Liiv

Since Specialization
Citations

This map shows the geographic impact of Innar Liiv'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 Innar Liiv with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Innar Liiv more than expected).

Fields of papers citing papers by Innar Liiv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Innar Liiv. 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 Innar Liiv. The network helps show where Innar Liiv may publish in the future.

Co-authors

The 20 scholars most cited alongside Innar Liiv, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Innar Liiv Line = papers co-authored together Innar Liiv links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010121
2 202023
3 202118
4 200717
5 20099
6 20166
7 20066
8 20075
9 20074
10 20114
11
Business Process Mining in Warehouses: a Case Study
20144
12 20194
13 20233
14 20232
15 20182
16 20192
17 20212
18 20231
19
Czekanowski-Bertin Learning Paradigm: A Discussion.
20071
20 20231

About Innar Liiv

Innar Liiv is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Information Systems, Management Science and Operations Research and Industrial and Manufacturing Engineering, having authored 28 papers that have together received 242 indexed citations. Recurring topics across this work include Data Management and Algorithms (3 papers), Building Energy and Comfort Optimization (3 papers), Image Processing and 3D Reconstruction (2 papers), Advanced Manufacturing and Logistics Optimization (2 papers), Time Series Analysis and Forecasting (2 papers), Data Visualization and Analytics (2 papers), Recommender Systems and Techniques (2 papers) and Digital Image Processing Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (79 citations), Public Administration (12 citations), Signal Processing (35 citations), Statistical and Nonlinear Physics (26 citations) and Artificial Intelligence (54 citations). Innar Liiv has collaborated with scholars based in Estonia, United States and United Kingdom. Frequent co-authors include Sadok Ben Yahia, Robert Aps, Laurence T. Kell, Hans Lassen, Tuukka Ruotsalo, Alar Kuusik, Tanel Tammet, Dirk Draheim, Targo Kalamees and Endrik Arumägi. Their work appears in journals such as ICES Journal of Marine Science, Biomedical Signal Processing and Control, Statistical Analysis and Data Mining The ASA Data Science Journal, European Journal of Social Work and Expert Systems with Applications.

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.

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