Martin Längkvist

According to our database, Martin Längkvist authored at least 22 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Machine Learning for Lithology Analysis using a Multi-Modal Approach of Integrating XRF and XCT data.

Suraj Neelakantan, Alexander Hansson, Jesper Norell, Johan Schött, Martin Längkvist, Amy Loutfi

Proceedings of the 14th Scandinavian Conference on Artificial Intelligence SCAI 2024, 2024

Affordance-Based Goal Imagination for Embodied AI Agents.

Victor Aregbede, Savitha Sam Abraham, Andreas Persson, Martin Längkvist, Amy Loutfi

Proceedings of the IEEE International Conference on Development and Learning, 2024

2023

An Intelligent Monitoring Algorithm to Detect Dependencies between Test Cases in the Manual Integration Process.

Cristina Landing, Xinrong Zhao, Martin Längkvist, Amy Loutfi

Proceedings of the IEEE International Conference on Software Testing, Verification and Validation, ICST 2023, 2023

2022

Empirical analysis of the convergence of Double DQN in relation to reward sparsity.

Samuel Blad, Martin Längkvist, Franziska Klügl, Amy Loutfi

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

Deep Learning based Aerial Image Segmentation for Computing Green Area Factor.

G. M. Atiqur Rahaman, Martin Längkvist, Amy Loutfi

Proceedings of the 10th European Workshop on Visual Information Processing, 2022

2020

Knowledge Representation and Reasoning Methods to Explain Errors in Machine Learning.

Marjan Alirezaie, Martin Längkvist, Amy Loutfi

Proceedings of the Knowledge Graphs for eXplainable Artificial Intelligence: Foundations, 2020

An Analysis of Fast Learning Methods for Classifying Forest Cover Types.

Hugo Sjöqvist, Martin Längkvist, Farrukh Javed

Appl. Artif. Intell., 2020

Cluster-Based Parallel Testing Using Semantic Analysis.

Cristina Landing, Sahar Tahvili, Hugo Haggren, Martin Längkvist, Auwn Muhammad, Amy Loutfi

Proceedings of the IEEE International Conference On Artificial Intelligence Testing, 2020

2019

Semantic referee: A neural-symbolic framework for enhancing geospatial semantic segmentation.

Marjan Alirezaie, Martin Längkvist, Michael Sioutis, Amy Loutfi

Semantic Web, 2019

Interactive user interface based on Convolutional Auto-encoders for annotating CT-scans.

Martin Längkvist, Jonas Widell, Per Thunberg, Amy Loutfi, Mats Lidén

CoRR, 2019

2018

A Deep Learning Approach with an Attention Mechanism for Automatic Sleep Stage Classification.

Martin Längkvist, Amy Loutfi

CoRR, 2018

Computer aided detection of ureteral stones in thin slice computed tomography volumes using Convolutional Neural Networks.

Martin Längkvist, Johan Jendeberg, Per Thunberg, Amy Loutfi, Mats Lidén

Comput. Biol. Medicine, 2018

2017

An Ontology-Based Reasoning Framework for Querying Satellite Images for Disaster Monitoring.

Marjan Alirezaie, Andrey Kiselev, Martin Längkvist, Franziska Klügl, Amy Loutfi

Sensors, 2017

Exploiting Context and Semantics for UAV Path-finding in an Urban Setting.

Marjan Alirezaie, Andrey Kiselev, Franziska Klügl, Martin Längkvist, Amy Loutfi

Proceedings of the 1st International Workshop on Application of Semantic Web technologies in Robotics co-located with 14th Extended Semantic Web Conference (ESWC 2017), 2017

2016

Classification and Segmentation of Satellite Orthoimagery Using Convolutional Neural Networks.

Martin Längkvist, Andrey Kiselev, Marjan Alirezaie, Amy Loutfi

Remote. Sens., 2016

Learning Actions to Improve the Perceptual Anchoring of Objects.

Andreas Persson, Martin Längkvist, Amy Loutfi

Frontiers Robotics AI, 2016

Open GeoSpatial Data as a Source of Ground Truth for Automated Labelling of Satellite Images.

Marjan Alirezaie, Martin Längkvist, Andrey Kiselev, Amy Loutfi

Proceedings of the Workshop on Spatial Data on the Web (SDW 2016) co-located with The 9th International Conference on Geographic Information Science (GIScience 2016), 2016

2015

Learning Feature Representations with a Cost-Relevant Sparse Autoencoder.

Martin Längkvist, Amy Loutfi

Int. J. Neural Syst., 2015

2014

Modeling time-series with deep networks.

Martin Längkvist

PhD thesis, 2014

A review of unsupervised feature learning and deep learning for time-series modeling.

Martin Längkvist, Lars Karlsson, Amy Loutfi

Pattern Recognit. Lett., 2014

2013

Fast Classification of Meat Spoilage Markers Using Nanostructured ZnO Thin Films and Unsupervised Feature Learning.

Martin Längkvist, Silvia Coradeschi, Amy Loutfi, John Bosco Balaguru Rayappan

Sensors, 2013

2012

Sleep Stage Classification Using Unsupervised Feature Learning.

Martin Längkvist, Lars Karlsson, Amy Loutfi

Adv. Artif. Neural Syst., 2012