Mats Sjöberg

887 citations
33 papers · 491 indexed · h-index 10
Topics
Advanced Image and Video Retrieval Techniques (12 papers)Video Analysis and Summarization (9 papers)Image Retrieval and Classification Techniques (7 papers)
Partner nations
FinlandRomaniaAustria

In The Last Decade

Mats Sjöberg

27 papers receiving 460 citations

Peers

Mats Sjöberg
Comparison fields: 5 of 83
  • Computer Vision and Pattern Recognition 175
  • Environmental Engineering 168
  • Pulmonary and Respiratory Medicine 125
  • Building and Construction 122
  • Artificial Intelligence 112
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Citations per field
00.5×12.2×
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Citations per year

Countries citing papers authored by Mats Sjöberg

Since Specialization
Citations

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

Fields of papers citing papers by Mats Sjöberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mats Sjöberg

This figure shows the co-authorship network connecting the top 25 collaborators of Mats Sjöberg. A scholar is included among the top collaborators of Mats Sjöberg 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 Mats Sjöberg. Mats Sjöberg 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
#WorkIndexed citations
1 0
2 2
3 7
4 17
5
The Predicting Media Memorability Task at MediaEval 2019.
7
6 16
7
The MediaEval 2016 Emotional Impact of Movies Task
26
8
RFA at MediaEval 2015 Affective Impact of Movies Task: A Multimodal Approach
16
9 22
10
The MediaEval 2014 Affect Task: Violent Scenes Detection
7
11
FAR at MediaEval 2014 Violent Scenes Detection: A Concept-based Fusion Approach.
5
12 24
13 1
14
FAR at MediaEval 2013 Violent Scenes Detection: Concept-based Violent Scenes Detection in Movies
9
15 5
16 1
17 5
18
PicSOM Experiments in TRECVID 2006
2
19
PicSOM Experiments in TRECVID 2005
2
20 251

About Mats Sjöberg

Mats Sjöberg is a scholar working on Computer Vision and Pattern Recognition, Information Systems and Management and Computer Science Applications, having authored 33 papers that have together received 491 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (12 papers), Video Analysis and Summarization (9 papers) and Image Retrieval and Classification Techniques (7 papers). The work is most often cited by research in Environmental Engineering (168 citations), Building and Construction (122 citations) and Computer Vision and Pattern Recognition (175 citations). Mats Sjöberg has collaborated with scholars based in Finland, Romania and Austria. Frequent co-authors include Mats Sandberg, Bogdan Ionescu, Jorma Laaksonen, Markus Schedl, Claire-Hélène Demarty, Markus Koskela, Emmanuel Dellandréa, Yoann Baveye, Pirkko Oittinen and Christel Chamaret. Their work appears in journals such as International Journal of Computer Vision, Building and Environment and Neurocomputing.

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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