J
Juan P. D'Amato
Researcher at National Scientific and Technical Research Council
Publications - 50
Citations - 119
Juan P. D'Amato is an academic researcher from National Scientific and Technical Research Council. The author has contributed to research in topics: Image segmentation & Video tracking. The author has an hindex of 5, co-authored 49 publications receiving 109 citations. Previous affiliations of Juan P. D'Amato include National University of Central Buenos Aires.
Papers
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Journal ArticleDOI
A CPU-GPU framework for optimizing the quality of large meshes
Juan P. D'Amato,M. VéNere +1 more
TL;DR: This paper will present a massive parallelization scheme for re-meshing with tetrahedral elements using the local modification algorithm, frequently used to improve the quality of elements once the mesh has been generated, and can be applied as a regeneration process.
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Multi-object segmentation framework using deformable models for medical imaging analysis.
Rafael Namías,Juan P. D'Amato,Mariana del Fresno,Marcelo Vénere,Nicola Pirró,Marc-Emmanuel Bellemare +5 more
TL;DR: A novel open-source framework called deformable model array (DMA) for the segmentation of multiple and complex structures of interest in different imaging modalities, which can implement complex object and multi-object segmentations in both 2D and 3D using the contextual information derived from the model interaction.
Journal Article
Mesh optimization with volume preservation using GPU
Juan P. D'Amato,P. Lotito +1 more
TL;DR: This work proposes an efficient and paralleliza- ble method to retrieve the local volume after per- forming successive operations, such as smoothing and topological changes that optimize the quality of the triangles.
Journal ArticleDOI
Plataforma abierta de gestión de cámaras IP y aplicaciones móviles para la seguridad civil ciudadana
TL;DR: This platform complements automated video analysis techniques with a communicational API for recording alarms or alerts from applications and allows real-time access to protection forces (police, fire brigades, and neighborhoods) to resources such as maps and videos.
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Real‐time aircraft radar simulator for a navy training system
TL;DR: This work proposes a new polygonal simplification method and a geometric classification algorithm in order to solve the intersections efficiently, which leads to high fidelity images and real‐time radar simulation, which operates at the specified 15 revolutions per minute rate.