Zobrazeno 1 - 10
of 499
pro vyhledávání: '"ŞAHİN, YUSUF"'
Point clouds are extensively employed in a variety of real-world applications such as robotics, autonomous driving and augmented reality. Despite the recent success of point cloud neural networks, especially for safety-critical tasks, it is essential
Externí odkaz:
http://arxiv.org/abs/2403.06698
Point clouds and meshes are widely used 3D data structures for many computer vision applications. While the meshes represent the surfaces of an object, point cloud represents sampled points from the surface which is also the output of modern sensors
Externí odkaz:
http://arxiv.org/abs/2403.06661
Publikováno v:
Porto, Portugal: SIS-Symmetry (2022) pp. 96-104
This study integrates artificial intelligence and computational design tools to extract information from architectural heritage. Photogrammetry-based point cloud models of brick walls from the Anatolian Seljuk period are analysed in terms of the inte
Externí odkaz:
http://arxiv.org/abs/2210.12856
Autor:
Kervarrec, Thibault, Cheok Lei, Kuan, Sohier, Pierre, Macagno, Nicolas, Jullie, Marie-Laure, Frouin, Eric, Goto, Keisuke, Taniguchi, Kohei, Hamard, Aymeric, Taillandier, Antoine, Tallet, Anne, Bonenfant, Christine, Sahin, Yusuf, Barry, Fatoumata, Taibjee, Saleem, Cokelaere, Kristof, Houben, Roland, Schrama, David, Nardin, Charlee, Aubin, Francois, Doucet, Laurent, Pissaloux, Daniel, Tirode, Franck, Fouchardière, Arnaud de la, Balme, Brigitte, Laurent-Roussel, Sara, Becker, Jürgen C., von Deimling, Andreas, Samimi, Mahtab, Cribier, Bernard, Battistella, Maxime, Calonje, Eduardo, Guyétan, Serge
Publikováno v:
In Modern Pathology November 2024 37(11)
Semi-automated minimization of brick-mortar segmentation errors in 3D historical wall reconstruction
Publikováno v:
In Automation in Construction November 2024 167
Publikováno v:
In Learning and Instruction December 2024 94
In recent years, deep learning based methods have shown success in essential medical image analysis tasks such as segmentation. Post-processing and refining the results of segmentation is a common practice to decrease the misclassifications originati
Externí odkaz:
http://arxiv.org/abs/2108.03117
Learning new representations of 3D point clouds is an active research area in 3D vision, as the order-invariant point cloud structure still presents challenges to the design of neural network architectures. Recent works explored learning either globa
Externí odkaz:
http://arxiv.org/abs/2012.04708
We propose a new approach for the problem of relative depth estimation from a single image. Instead of directly regressing over depth scores, we formulate the problem as estimation of a probability distribution over depth and aim to learn the paramet
Externí odkaz:
http://arxiv.org/abs/2010.07091
Deep neural network training without pre-trained weights and few data is shown to need more training iterations. It is also known that, deeper models are more successful than their shallow counterparts for semantic segmentation task. Thus, we introdu
Externí odkaz:
http://arxiv.org/abs/2009.06469