52 citations · 85 across the 17 of their papers we have counts for
18 papers · 1 filter
Utilizing dataset affinity prediction in object detection to assess training data
Stefan Becker, Jens Bayer, Ronny Hug +2
Data pooling offers various advantages, such as increasing the sample size, improving generalization, reducing sampling bias, and addressing data sparsity and quality, but it is no…
Eigenpatches -- Adversarial Patches from Principal Components
Jens Bayer, Stefan Becker, David Münch +1
Adversarial patches are still a simple yet powerful white box attack that can be used to fool object detectors by suppressing possible detections. The patches of these so-called ev…
Geo-Tiles for Semantic Segmentation of Earth Observation Imagery
Sebastian Bullinger, Florian Fervers, Christoph Bodensteiner +1
To cope with the high requirements during the computation of semantic segmentations of earth observation imagery, current state-of-the-art pipelines divide the corresponding data i…
READMem: Robust Embedding Association for a Diverse Memory in Unconstrained Video Object Segmentation
Stéphane Vujasinović, Sebastian Bullinger, Stefan Becker +3
We present READMem (Robust Embedding Association for a Diverse Memory), a modular framework for semi-automatic video object segmentation (sVOS) methods designed to handle unconstra…
A Comparison of Deep Saliency Map Generators on Multispectral Data in Object Detection
Jens Bayer, David Münch, Michael Arens
Deep neural networks, especially convolutional deep neural networks, are state-of-the-art methods to classify, segment or even generate images, movies, or sounds. However, these me…
Generating Synthetic Training Data for Deep Learning-Based UAV Trajectory Prediction
Stefan Becker, Ronny Hug, Wolfgang Hübner +2
Deep learning-based models, such as recurrent neural networks (RNNs), have been applied to various sequence learning tasks with great success. Following this, these models are incr…