Zobrazeno 1 - 10
of 2 002
pro vyhledávání: '"Kuijper P"'
Autor:
Baudoin, Fabrice, Kuijper, Teije
We give explicit formulas and asymptotics for the distribution of the index of the Brownian loop in the following geometrical settings: the complex projective line from which two points have been removed; the complex hyperbolic line from which one po
Externí odkaz:
http://arxiv.org/abs/2410.06824
Publikováno v:
Machine.Learning.for.Biomedical.Imaging. 2 (2024)
Convolutional neural networks (CNNs) achieve prevailing results in segmentation tasks nowadays and represent the state-of-the-art for image-based analysis. However, the understanding of the accurate decision-making process of a CNN is rather unknown.
Externí odkaz:
http://arxiv.org/abs/2409.20287
6D object pose estimation is the problem of identifying the position and orientation of an object relative to a chosen coordinate system, which is a core technology for modern XR applications. State-of-the-art 6D object pose estimators directly predi
Externí odkaz:
http://arxiv.org/abs/2409.11819
Autor:
Knauthe, Volker, Rak, Arne, Wirth, Tristan, Pöllabauer, Thomas, Metzler, Simon, Kuijper, Arjan, Fellner, Dieter W.
Semantic Image Segmentation facilitates a multitude of real-world applications ranging from autonomous driving over industrial process supervision to vision aids for human beings. These models are usually trained in a supervised fashion using example
Externí odkaz:
http://arxiv.org/abs/2405.12864
Autor:
Knauthe, Volker, Weitz, Paul, Pöllabauer, Thomas, Wirth, Tristan, Rak, Arne, Kuijper, Arjan, Fellner, Dieter W.
Computer vision techniques are on the rise for industrial applications, like process supervision and autonomous agents, e.g., in the healthcare domain and dangerous environments. While the general usability of these techniques is high, there are stil
Externí odkaz:
http://arxiv.org/abs/2405.12861
Deep Neural Networks (DNNs) require large amounts of annotated training data for a good performance. Often this data is generated using manual labeling (error-prone and time-consuming) or rendering (requiring geometry and material information). Both
Externí odkaz:
http://arxiv.org/abs/2405.07653
We propose a novel, lightweight supervised dictionary learning framework for text classification based on data compression and representation. This two-phase algorithm initially employs the Lempel-Ziv-Welch (LZW) algorithm to construct a dictionary f
Externí odkaz:
http://arxiv.org/abs/2405.01584
Publikováno v:
21st Eurographics Workshop on Graphics and Cultural Heritage (GCH 2023)
Estimating the 3D shape of an object using a single image is a difficult problem. Modern approaches achieve good results for general objects, based on real photographs, but worse results on less expressive representations such as historic sketches. O
Externí odkaz:
http://arxiv.org/abs/2402.08310
Estimating the 6D pose of objects accurately, quickly, and robustly remains a difficult task. However, recent methods for directly regressing poses from RGB images using dense features have achieved state-of-the-art results. Stereo vision, which prov
Externí odkaz:
http://arxiv.org/abs/2402.05610
Autor:
de Kuijper, Kees, Diwan, Rishank, Pal, Partha Sarathi, Ritter, Andreas, Parkinson, Pablo M. Saz, Kong, Andy C. T., Parker, Quentin A.
Publikováno v:
Exp Astron 57, 16 (2024)
The low-energy $\gamma$-ray (0.1-30 MeV) sky has been relatively unexplored since the decommissioning of the COMPTEL instrument on the Compton Gamma-Ray Observatory (CGRO) satellite in 2000. However, the study of this part of the energy spectrum (the
Externí odkaz:
http://arxiv.org/abs/2401.09735