Markus Thom

According to our database1, Markus Thom authored at least 16 papers between 2011 and 2018.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2018
A random finite set approach for dynamic occupancy grid maps with real-time application.
Int. J. Robotics Res., 2018

2017
Rapid Exact Signal Scanning With Deep Convolutional Neural Networks.
IEEE Trans. Signal Process., 2017

2016
Adaptive learning based on guided exploration for decision making at roundabouts.
Proceedings of the 2016 IEEE Intelligent Vehicles Symposium, 2016

2015
Sparse neural networks.
PhD thesis, 2015

Efficient Dictionary Learning with Sparseness-Enforcing Projections.
Int. J. Comput. Vis., 2015

A Theory for Rapid Exact Signal Scanning with Deep Multi-Scale Convolutional Neural Networks.
CoRR, 2015

Semi-Markov Process Based Localization Using Radar in Dynamic Environments.
Proceedings of the IEEE 18th International Conference on Intelligent Transportation Systems, 2015

2014
Fusion of laser and monocular camera data in object grid maps for vehicle environment perception.
Proceedings of the 17th International Conference on Information Fusion, 2014

2013
Sparse activity and sparse connectivity in supervised learning.
J. Mach. Learn. Res., 2013

Efficient Sparseness-Enforcing Projections
CoRR, 2013

Convolutional Neural Networks for night-time animal orientation estimation.
Proceedings of the 2013 IEEE Intelligent Vehicles Symposium (IV), 2013

Learning convolutional neural networks from few samples.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

Image compression with discriminative dictionaries.
Proceedings of the IEEE Third International Conference on Consumer Electronics, 2013

2012
Influence of image compression on cascade classifier components.
Proceedings of the 10th IEEE Jubilee International Symposium on Intelligent Systems and Informatics, 2012

2011
Supervised Matrix Factorization with sparseness constraints and fast inference.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Training of Sparsely Connected MLPs.
Proceedings of the Pattern Recognition - 33rd DAGM Symposium, Frankfurt/Main, Germany, August 31, 2011


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