Dominik Kryzia
Biographic Data
| ID | 9965555 |
|---|---|
| NAME | Dominik Kryzia |
| GIVEN NAMES | Dominik |
| FAMILY NAME | Kryzia |
| SIGNATURE | KRYZIA D |
| AFFILIATIONS | Mineral and Energy Economy Research Institute of the Polish Academy of Sciences |
| ORCID | 0000-0003-0639-3485 |
| VERIFIED | Yes |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 1 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2026 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Analysis of Using Machine Learning Application Possibilities for the Detection and Classification of Topographic Objects
The growing availability of spatial data from remote sensing, laser scanning (LiDAR), and photogrammetric techniques stimulates the dynamic development of methods for the automatic detection and classification of topographic objects. In recent years, both classical machine learning (ML) algorithms and deep learning (DL) methods have found wide application in the analysis of large and complex data sets. Despite significant achievements, literature…
No prominent works on this page.
Analysis of Using Machine Learning Application Possibilities for the Detection and Classification of Topographic Objects
The growing availability of spatial data from remote sensing, laser scanning (LiDAR), and photogrammetric techniques stimulates the dynamic development of methods for the automatic detection and classification of topographic objects. In recent years, both classical machine learning (ML) algorithms and deep learning (DL) methods have found wide application in the analysis of large and complex data sets. Despite significant achievements, literature…
Aerial image (1 work) · Automated Road and Building Extraction (1 work) · Deep learning (1 work) · Digital elevation model (1 work) · Object detection (1 work) · Photogrammetry (1 work) · Raster graphics (1 work) · Remote Sensing and LiDAR Applications (1 work) · Remote-Sensing Image Classification (1 work) · Segmentation (1 work)