Abstract
AbstractThis research focuses on studying low-cost techniques for rapid mapping, utilizing sensors equipped on smartphones. These devices were installed on a radio-controlled vehicle to conduct an experimental campaign aimed at evaluating the performance of LiDAR sensor. By collecting data, machine learning algorithms were employed for the detection of architectural defects.
Funder
Università degli Studi di Napoli Federico II
Publisher
Springer Science and Business Media LLC
Subject
Visual Arts and Performing Arts,General Mathematics,Architecture
Reference10 articles.
1. Albawi, Saad, Tareq Abed Mohammed, and Saad Al-Zawi. 2017. Understanding of a convolutional neural network. 2017 International Conference on Engineering and Technology (ICET): 1–6.
2. Falcone, Marika, and Massimiliano Campi. 2021. Il Quadriportico della Cattedrale di S. Matteo: sensori low cost per rilievi di rapid mapping/ The Quadriportico of the Cathedral of S. Matteo: Low-cost Sensors for Rapid Mapping Surveys. In Connettere. Un disegno per annodare e tessere. Linguaggi Distanze Tecnologie. Atti del 42° Convegno Internazionale dei Docenti delle Discipline della Rappresentazione/Connecting. Drawing for weaving relationship. Languages Distances Technologies. Proceedings of the 42th International Conference of Representation Disciplines Teachers, 2283–2300. Milano: FrancoAngeli.
3. Fassmeyer, Pascal, Felix Kortmann, Paul Drews, and Burkhardt Funk. 2021. Towards a Camera-Based Road Damage Assessment and Detection for Autonomous Vehicles: Applying Scaled-YOLO and CVAE-WGAN. 2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall). https://doi:https://doi.org/10.1109/VTC2021-Fall52928.2021.9625213.
4. Fiorini, Andrea. 2022. Scansioni dinamiche in archeologia dell’architettura: test e valutazioni metriche del sensore LiDAR di Apple. Archeologia e Calcolatori. 33.1:35-54
5. Kagaya, Hokuto, Kiyoharu Aizawa, and Makoto Ogawa. 2014. Food detection and recognition using convolutional neural network. Proceedings of the 22nd ACM international conference on Multimedia: 1085–1088.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Predicting Architectural Decay by AI Applied to 3D Survey;Digital Innovations in Architecture, Engineering and Construction;2024