APPLICATION OF MACHINE AND DEEP LEARNING STRATEGIES FOR THE CLASSIFICATION OF HERITAGE POINT CLOUDS

24 citations as recorded by crossref.

1. Application of Territorial Laser Scanning in 3D Modeling of Traditional Village: A Case Study of Fenghuang Village in China G. Lin et al. 10.3390/ijgi10110770
2. A Hierarchical Machine Learning Approach for Multi-Level and Multi-Resolution 3D Point Cloud Classification S. Teruggi et al. 10.3390/rs12162598
3. Ming and Qing Dynasty Official-Style Architecture Roof Types Classification Based on the 3D Point Cloud Y. Dong et al. 10.3390/ijgi10100650
4. Research Ancient Artifact Identification Methods under Intelligent Perception and Recognition Technology Q. Zhao & V. Kumaravelu 10.1155/2021/9971343
5. Deep Learning Inspired Object Consolidation Approaches Using LiDAR Data for Autonomous Driving: A Review M. Mekala et al. 10.1007/s11831-021-09670-y
6. Solid Model Generation for Digitized Organic Bodies via T-Splines L. Barazzetti 10.3390/heritage3030035
7. An Open System for Collection and Automatic Recognition of Pottery through Neural Network Algorithms M. Gualandi et al. 10.3390/heritage4010008
8. Metodología de captura y procesado para el desarrollo de una base de datos gráfica 3D del patrimonio arquitectónico M. Quintilla Castán & L. Agustín Hernández 10.37558/gec.v21i1.1048
9. Measuring rock slope damage on rubble mound breakwater through digital photogrammetry S. Marino et al. 10.1016/j.measurement.2023.112656
10. Machine Learning Generalisation across Different 3D Architectural Heritage E. Grilli & F. Remondino 10.3390/ijgi9060379
11. Multiclass semantic segmentation for digitisation of movable heritage using deep learning techniques G. Patrucco & F. Setragno 10.4995/var.2021.15329
12. Multidisciplinary Pattern Recognition applications: A review M. Paolanti & E. Frontoni 10.1016/j.cosrev.2020.100276
13. 3D Documentation with TLS of Caliphal Gate (Ceuta, Spain) R. Pérez-Álvarez et al. 10.3390/app10155377
14. Virtual Disassembling of Historical Edifices: Experiments and Assessments of an Automatic Approach for Classifying Multi-Scalar Point Clouds into Architectural Elements A. Murtiyoso & P. Grussenmeyer 10.3390/s20082161
15. From the Semantic Point Cloud to Heritage-Building Information Modeling: A Semiautomatic Approach Exploiting Machine Learning V. Croce et al. 10.3390/rs13030461
16. Three-Dimensional Point Cloud Semantic Segmentation for Cultural Heritage: A Comprehensive Review S. Yang et al. 10.3390/rs15030548
17. Aerial Point Cloud Classification Using an Alternative Approach for the Dynamic Computation of K-Nearest Neighbors I. Pârvu et al. 10.2478/jaes-2020-0023
18. Comparing Machine and Deep Learning Methods for Large 3D Heritage Semantic Segmentation F. Matrone et al. 10.3390/ijgi9090535
19. Transfer learning and performance enhancement techniques for deep semantic segmentation of built heritage point clouds F. Matrone & M. Martini 10.4995/var.2021.15318
20. A Multilevel Multiresolution Machine Learning Classification Approach: A Generalization Test on Chinese Heritage Architecture K. Zhang et al. 10.3390/heritage5040204
21. Point Cloud Semantic Segmentation Using a Deep Learning Framework for Cultural Heritage R. Pierdicca et al. 10.3390/rs12061005
22. Application of Deep Learning Approach for the Classification of Buildings’ Degradation State in a BIM Methodology F. Rodrigues et al. 10.3390/app12157403
23. Two-Dimensional Shape Analysis of Complex Geometry Based on Photogrammetric Models of Iconostases I. Đurić et al. 10.3390/app11157042
24. The Point Cloud Semantic Segmentation Method for the Ming and Qing Dynasties’ Official-Style Architecture Roof Considering the Construction Regulations Y. Dong et al. 10.3390/ijgi11040214