Zobrazeno 1 - 10
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pro vyhledávání: '"A Alliez"'
Bayesian Optimal Experimental Design (BOED) is a powerful tool to reduce the cost of running a sequence of experiments. When based on the Expected Information Gain (EIG), design optimization corresponds to the maximization of some intractable expecte
Externí odkaz:
http://arxiv.org/abs/2410.11826
We present a novel approach for generating isotropic surface triangle meshes directly from unoriented 3D point clouds, with the mesh density adapting to the estimated local feature size (LFS). Popular reconstruction pipelines first reconstruct a dens
Externí odkaz:
http://arxiv.org/abs/2403.13924
Although polygon meshes have been a standard representation in geometry processing, their irregular and combinatorial nature hinders their suitability for learning-based applications. In this work, we introduce a novel learnable mesh representation t
Externí odkaz:
http://arxiv.org/abs/2403.12870
Publikováno v:
Proceedings of the 41st International Conference on Machine Learning, 2024
We propose a new procedure named PASOA, for Bayesian experimental design, that performs sequential design optimization by simultaneously providing accurate estimates of successive posterior distributions for parameter inference. The sequential design
Externí odkaz:
http://arxiv.org/abs/2402.07160
In stark contrast to the case of images, finding a concise, learnable discrete representation of 3D surfaces remains a challenge. In particular, while polygon meshes are arguably the most common surface representation used in geometry processing, the
Externí odkaz:
http://arxiv.org/abs/2308.14616
This paper proposes BPNet, a novel end-to-end deep learning framework to learn B\'ezier primitive segmentation on 3D point clouds. The existing works treat different primitive types separately, thus limiting them to finite shape categories. To addres
Externí odkaz:
http://arxiv.org/abs/2307.04013
Publikováno v:
BMC Oral Health, Vol 23, Iss 1, Pp 1-11 (2023)
Abstract Objectives This scoping review aimed to assess the current state of knowledge regarding the relationship between bruxism and changes in density or volume of mandibular bone, based on medical imaging. Methods Literature review was conducted f
Externí odkaz:
https://doaj.org/article/ead1a98207d44507ad268c30b6537261
The domain adaptation of satellite images has recently gained an increasing attention to overcome the limited generalization abilities of machine learning models when segmenting large-scale satellite images. Most of the existing approaches seek for a
Externí odkaz:
http://arxiv.org/abs/2005.06216
Domain adaptation for semantic segmentation has recently been actively studied to increase the generalization capabilities of deep learning models. The vast majority of the domain adaptation methods tackle single-source case, where the model trained
Externí odkaz:
http://arxiv.org/abs/2004.06402
Although convolutional neural networks have been proven to be an effective tool to generate high quality maps from remote sensing images, their performance significantly deteriorates when there exists a large domain shift between training and test da
Externí odkaz:
http://arxiv.org/abs/2002.05925