Martin Längkvist

2.2k citations
26 papers · 1.5k indexed · 1 hit paper · h-index 9

Martin Längkvist

25 papers receiving 1.5k citations

Hit Papers

A review of unsupervised feature learning and deep learni...8742014202620182022250500750

Peers

Martin Längkvist
Comparison fields: 5 of 151
  • Signal Processing 295
  • Media Technology 161
  • Cognitive Neuroscience 230
  • Artificial Intelligence 379
  • Computer Vision and Pattern Recognition 234
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Manel Martínez‐Ramón United States
Birmohan Singh India
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Mohammad Hossein Rafiei United States
Ming Zong China
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Hemant Ghayvat India
G. R. Sinha India
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Citations per field
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Citations per year

Countries citing papers authored by Martin Längkvist

Since Specialization
Citations

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

Fields of papers citing papers by Martin Längkvist

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 17 scholars most cited alongside Martin Längkvist, 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 Martin Längkvist Line = papers co-authored together Martin Längkvist links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20248
3 20241
4 20245
5 20232
6 20232
7 20223
8 20221
9 20207
10
A Symbolic Approach for Explaining Errors in Image Classification Tasks
20185
11 201865
12
Exploiting Context and Semantics for UAV Path-finding in an Urban Setting
20173
13
Interactive Learning with Convolutional Neural Networks for Image Labeling
20165
14
Open GeoSpatial Data as a Source of Ground Truth for Automated Labelling of Satellite Images
20163
15 201421
16
Modeling time-series with deep networks
20144
17
Not all signals are created equal : Dynamic objective auto-encoder for multivariate data
20122
18
Learning Representations with a Dynamic Objective Sparse Autoencoder
20121
19
Unsupervised feature learning for electronic nose data applied to Bacteria Identification in Blood.
201133
20
Online Identification of Friction Coefficients in an Industrial Robot
20090

About Martin Längkvist

Martin Längkvist is a scholar working on Signal Processing, Artificial Intelligence and Media Technology, having authored 26 papers that have together received 1.5k indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (4 papers), Anomaly Detection Techniques and Applications (4 papers), Advanced Chemical Sensor Technologies (3 papers), Remote-Sensing Image Classification (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Analytical Chemistry and Chromatography (2 papers), Remote Sensing in Agriculture (2 papers) and Human Pose and Action Recognition (2 papers). The work is most often cited by research in Signal Processing (295 citations), Media Technology (161 citations) and Cognitive Neuroscience (230 citations). Martin Längkvist has collaborated with scholars based in Sweden, Denmark and Germany. Frequent co-authors include Amy Loutfi, Lars Karlsson, Marjan Alirezaie, Andrey Kiselev, Mats Lidén, Per Thunberg, John Bosco Balaguru Rayappan, Silvia Coradeschi, Franziska Klügl and Farrukh Javed. Their work appears in journals such as SHILAP Revista de lepidopterología, Sensors and Remote Sensing.

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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