Magnus Johnsson

1.1k citations
46 papers · 717 indexed · h-index 15
Topics
Robot Manipulation and Learning (13 papers)Neural Networks and Applications (10 papers)Tactile and Sensory Interactions (10 papers)
Partner nations
SwedenSpainIran

In The Last Decade

Magnus Johnsson

45 papers receiving 659 citations

Peers

Magnus Johnsson
Comparison fields: 5 of 126
  • Artificial Intelligence 259
  • Cognitive Neuroscience 140
  • Computer Vision and Pattern Recognition 128
  • Control and Systems Engineering 113
  • Physiology 62
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Countries citing papers authored by Magnus Johnsson

Since Specialization
Citations

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

Fields of papers citing papers by Magnus Johnsson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Magnus Johnsson

This figure shows the co-authorship network connecting the top 25 collaborators of Magnus Johnsson. A scholar is included among the top collaborators of Magnus Johnsson 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 Magnus Johnsson. Magnus Johnsson 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 4
2 4
3 43
4
Simulating Actions with the Associative Self-Organizing Map
3
5 15
6 1
7 9
8 26
9
Supervised Architectures for Internal Simulation of Perceptions and Actions
5
10
Supervised SOM Based Architecture versus Multilayer Perceptron and RBF Networks
11
11
Experiments with Self-Organizing Systems for Texture and Hardness Perception
4
12 25
13
Associating SOM Representations of Haptic Submodalities
6
14
Touch Perception with SOM, Growing Cell Structures and Growing Grids
3
15 10
16
Ikaros: Building Cognitive Models for Robots.
1
17
Experiments with Proprioception in a Self-Organizing System for Haptic Perception
20
18 27
19
A Robot Hand with T-MPSOM Neural Networks in a Model of the Human Haptic System
5
20 49

About Magnus Johnsson

Magnus Johnsson is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Cognitive Neuroscience, having authored 46 papers that have together received 717 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (13 papers), Neural Networks and Applications (10 papers) and Tactile and Sensory Interactions (10 papers). The work is most often cited by research in Health Informatics (17 citations), Health Information Management (40 citations) and Artificial Intelligence (259 citations). Magnus Johnsson has collaborated with scholars based in Sweden, Spain and Iran. Frequent co-authors include David Gil, Christian Balkenius, Joaquı́n De Juan, María José Gómez‐Torres, Higinio Mora, Daniel Ruíz Fernández, Juan Manuel García‐Chamizo, Julian Szymański, Peter Gärdenfors and P. Simonsson. Their work appears in journals such as Expert Systems with Applications, Sensors and Biology of Reproduction.

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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