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Digital Twin of a Smart Plant Factory for Plant Phenotyping : Data assimilation between measured and simulated 3D point cloud data in the CPlantBox FSPM

• Authors : Bouvry, Arnaud; Lebeau, Frédéric

Subjects: digital twin; data simulation; controlled environment agriculture

• Source: 10th Conference on Functional-Structural Plant Models (FSPM2023), Berlin, Germany [DE], 27/3/2023-31/3/2023

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LibCOS: Enabling Converged HPC and Cloud Data Stores with MPI

• Authors : Araújo De Medeiros, Daniel; Markidis, Stefano; Peng, Ivy Bo

Subjects: Ceph; MPI; object storage

• Source: Proceedings of International Conference on High Performance Computing in Asia-Pacific Region, HPC Asia 2023. :106-116

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Examining the Challenges of Cloud Data Management Usage in the South African Construction Industry

• Authors : Wanda Buhle Mpingana; OPEOLUWA AKINRADEWO; Clinton Aigbavboa

Subjects: Sustainable architecture; Sustainable design; Environmentally sustainable engineering

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Demonstrating MAST: an efficient system for point cloud data analytics

• Authors : Li, Jiangneng; Yuan, Haitao; Wang, Jie ...

Subjects: Computer and Information Science; Point cloud data query processing; DB4AI

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Automatic extraction and management of semantics within point cloud data

• Authors : Poux, Florent

Subjects: 3D; Point Cloud; Semantics

• Source: NCG Point Clouds Seminar, Virtual Conference (Twente - TU Delft), Netherlands [NL], 28 mai 2020

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Examining the Challenges of Cloud Data Management Usage in the South African Construction Industry

• Authors : Wanda Buhle Mpingana; OPEOLUWA AKINRADEWO; Clinton Aigbavboa

Subjects: Sustainable architecture; Sustainable design; Environmentally sustainable engineering

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A Framework for Building Point Cloud Cleaning, Plane Detection and Semantic Segmentation ; A Framework for Building Point Cloud Cleaning, Plane Detection and Semantic Segmentation: This paper presents a framework to address the challenges involved in building point cloud cleaning, plane detection, and semantic segmentation, with the ultimate goal of enhancing building modeling. We focus in the cleaning stage on removing outliers from the acquired point cloud data by employing an adaptive threshold technique based on z-score measure. Following the cleaning process, we perform plane detection using the robust RANSAC paradigm. The goal is to carry out multiple plane segmentations, and to classify segments into distinct categories, such as floors, ceilings, and walls. The resulting segments can generate accurate and detailed point clouds representing the building's architectural elements. Moreover, we address the problem of semantic segmentation, which plays a vital role in the identification and classification of different components within the building, such as walls, windows, doors, roofs, and objects. Inspired by the PointNet architecture, we propose a deep learning architecture for efficient semantic segmentation in buildings. The results demonstrate the effectiveness of the proposed framework in handling building modeling tasks, paving the way for improved accuracy and efficiency in the field of building modelization.

• Authors : Mourchid, Youssef;

Subjects: deep learning; semantic segmentation; outlier removalGizeh; Egypt

• Source: ACS/IEEE International Conference on Computer Systems and Applications (AICCSA) 2023 ; https://hal.science/hal-04973758 ; ACS/IEEE International Conference on Computer Systems and Applications

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Leveraging CVAE for joint configuration estimation of multifingered grippers from point cloud data

• Authors : Merand, Julien; Meden, Boris; Grossard, Mathieu ...

Subjects: [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]; [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Los Angeles; United States

• Source: Proceedings of the 2025 IEEE 21st International Conference on Automation Science and Engineering (CASE) ; CASE 2025 - IEEE 21st International Conference on Automation Science and Engineering ;

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Automatic Reconstruction of Aligned Indoor Building and Façade Elements from Point Cloud Data

• Authors : Wang, Mudan; Pan, Yuandong; Chan, Anson

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MODEL FOR REASONING FROM SEMANTICALLY RICH POINT CLOUD DATA

• Authors : Poux, Florent; Neuville, Romain; Hallot, Pierre

Subjects: point cloud; data model; classification

• Source: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, IV-4/W5, 107-115 (2017-10-26); 12th 3D Geoinfo Conference, Melbourne, Australia [AU], 26 octobre 2017 au 27 octobre

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