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

34 citations as recorded by crossref.

1. A Hierarchical Machine Learning Approach for Multi-Level and Multi-Resolution 3D Point Cloud Classification S. Teruggi et al. 10.3390/rs12162598
2. Land Cover and Landscape Structural Changes Using Extreme Gradient Boosting Random Forest and Fragmentation Analysis C. Matyukira & P. Mhangara 10.3390/rs15235520
3. Historic Built Environment Assessment and Management by Deep Learning Techniques: A Scoping Review V. Giannuzzi & F. Fatiguso 10.3390/app14167116
4. Convolutional Neural Networks and Regression Algorithms Supporting Buildings Facility Management R. Matos et al. 10.3390/buildings13112805
5. Automatic generation of synthetic heritage point clouds: Analysis and segmentation based on shape grammar for historical vaults C. Battini et al. 10.1016/j.culher.2023.10.003
6. Ming and Qing Dynasty Official-Style Architecture Roof Types Classification Based on the 3D Point Cloud Y. Dong et al. 10.3390/ijgi10100650
7. Research Ancient Artifact Identification Methods under Intelligent Perception and Recognition Technology Q. Zhao & V. Kumaravelu 10.1155/2021/9971343
8. Deep Learning Inspired Object Consolidation Approaches Using LiDAR Data for Autonomous Driving: A Review M. Mekala et al. 10.1007/s11831-021-09670-y
9. Solid Model Generation for Digitized Organic Bodies via T-Splines L. Barazzetti 10.3390/heritage3030035
10. Semantic segmentation of point clouds of ancient buildings based on weak supervision J. Zhao et al. 10.1186/s40494-024-01353-8
11. MonuNet: a high performance deep learning network for Kolkata heritage image classification A. Sasithradevi et al. 10.1186/s40494-024-01340-z
12. Deep learning methods applied to digital elevation models: state of the art J. Ruiz-Lendínez et al. 10.1080/10106049.2023.2252389
13. Enhancing preservation outcomes for architectural heritage buildings through machine learning-driven future search optimization S. Abusaleh 10.1007/s42107-024-01112-x
14. An Open System for Collection and Automatic Recognition of Pottery through Neural Network Algorithms M. Gualandi et al. 10.3390/heritage4010008
15. 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
16. Deep learning based approaches from semantic point clouds to semantic BIM models for heritage digital twin X. Pan et al. 10.1186/s40494-024-01179-4
17. Measuring rock slope damage on rubble mound breakwater through digital photogrammetry S. Marino et al. 10.1016/j.measurement.2023.112656
18. Machine Learning Generalisation across Different 3D Architectural Heritage E. Grilli & F. Remondino 10.3390/ijgi9060379
19. Multiclass semantic segmentation for digitisation of movable heritage using deep learning techniques G. Patrucco & F. Setragno 10.4995/var.2021.15329
20. Multidisciplinary Pattern Recognition applications: A review M. Paolanti & E. Frontoni 10.1016/j.cosrev.2020.100276
21. 3D Documentation with TLS of Caliphal Gate (Ceuta, Spain) R. Pérez-Álvarez et al. 10.3390/app10155377
22. Machine Learning for the Semi-Automatic 3D Decay Segmentation and Mapping of Heritage Assets R. Galantucci et al. 10.1080/15583058.2023.2287152
23. 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
24. From the Semantic Point Cloud to Heritage-Building Information Modeling: A Semiautomatic Approach Exploiting Machine Learning V. Croce et al. 10.3390/rs13030461
25. Three-Dimensional Point Cloud Semantic Segmentation for Cultural Heritage: A Comprehensive Review S. Yang et al. 10.3390/rs15030548
26. 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
27. Application of computer vision techniques for 3D matching and retrieval of archaeological objects D. Jiménez-Badillo et al. 10.12688/f1000research.127095.2
28. Comparing Machine and Deep Learning Methods for Large 3D Heritage Semantic Segmentation F. Matrone et al. 10.3390/ijgi9090535
29. Transfer learning and performance enhancement techniques for deep semantic segmentation of built heritage point clouds F. Matrone & M. Martini 10.4995/var.2021.15318
30. A Multilevel Multiresolution Machine Learning Classification Approach: A Generalization Test on Chinese Heritage Architecture K. Zhang et al. 10.3390/heritage5040204
31. Point Cloud Semantic Segmentation Using a Deep Learning Framework for Cultural Heritage R. Pierdicca et al. 10.3390/rs12061005
32. Application of Deep Learning Approach for the Classification of Buildings’ Degradation State in a BIM Methodology F. Rodrigues et al. 10.3390/app12157403
33. Two-Dimensional Shape Analysis of Complex Geometry Based on Photogrammetric Models of Iconostases I. Đurić et al. 10.3390/app11157042
34. 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