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- Center for Integrated Quantum Science and TechnologyDE57 papers
- Centre National de la Recherche ScientifiqueFR19 papers
- Helmholtz-Institute UlmDE14 papers
- Leibniz University HannoverDE14 papers
- Imperial College LondonGB13 papers
- Hebrew University of JerusalemIL12 papers
- Technische Hochschule UlmDE12 papers
- National University of SingaporeSG10 papers
- Universitat Autònoma de BarcelonaES10 papers
- Technical University of MunichDE9 papers
- University of MilanIT9 papers
- Centre for Quantum TechnologiesSG8 papers
12 papers · 1 filter
Automatic Bat Call Classification using Transformer Networks
Frank Fundel, Daniel A. Braun, Sebastian Gottwald
Automatically identifying bat species from their echolocation calls is a difficult but important task for monitoring bats and the ecosystem they live in. Major challenges in automa…
Self-Supervised Pre-Training with Contrastive and Masked Autoencoder Methods for Dealing with Small Datasets in Deep Learning for Medical Imaging
Daniel Wolf, Tristan Payer, Catharina Silvia Lisson +4
Deep learning in medical imaging has the potential to minimize the risk of diagnostic errors, reduce radiologist workload, and accelerate diagnosis. Training such deep learning mod…
Gesture Recognition with Keypoint and Radar Stream Fusion for Automated Vehicles
Adrian Holzbock, Nicolai Kern, Christian Waldschmidt +2
We present a joint camera and radar approach to enable autonomous vehicles to understand and react to human gestures in everyday traffic. Initially, we process the radar data with…
SCENE: Reasoning about Traffic Scenes using Heterogeneous Graph Neural Networks
Thomas Monninger, Julian Schmidt, Jan Rupprecht +5
Understanding traffic scenes requires considering heterogeneous information about dynamic agents and the static infrastructure. In this work we propose SCENE, a methodology to enco…
Radial Basis Function Networks for Convolutional Neural Networks to Learn Similarity Distance Metric and Improve Interpretability
Mohammadreza Amirian, Friedhelm Schwenker
Radial basis function neural networks (RBFs) are prime candidates for pattern classification and regression and have been used extensively in classical machine learning application…
Detection of Condensed Vehicle Gas Exhaust in LiDAR Point Clouds
Aldi Piroli, Vinzenz Dallabetta, Marc Walessa +3
LiDAR sensors used in autonomous driving applications are negatively affected by adverse weather conditions. One common, but understudied effect, is the condensation of vehicle gas…