Laszlo Bertalan
Biographic Data
| ID | 6106691 |
|---|---|
| NAME | Laszlo Bertalan |
| GIVEN NAMES | Laszlo |
| FAMILY NAME | Bertalan |
| SIGNATURE | BERTALAN L |
| AFFILIATIONS | University of Debrecen |
| ORCID | 0000-0002-5963-2710 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1989 |
| LATEST PUBLICATION YEAR | 2020 |
| H-INDEX | 0 |
Machine Learning for Gully Feature Extraction Based on a Pan-Sharpened Multispectral Image
Gullies reduce both the quality and quantity of productive land, posing a serious threat to sustainable agriculture, hence, food security. Machine Learning (ML) algorithms are essential tools in the identification of gullies and can assist in strategic decision-making relevant to soil conservation. Nevertheless, accurate identification of gullies is a function of the selected ML algorithms, the image and number of classes used, i.e., binary (two …
Confirmation of a theory
Fluvial geomorphologists have tried to describe the outstanding tectonically affected avulsion process of Tisza River at the Great Hungarian Plain by various theoretical concepts.Flume experiments provide the ability to examine the main characteristic processes of a highlighted surface development theory under controlled settings within an accelerated time scale.Our goal was to reconstruct and refine these hypotheses from a new experimental point…
Economy and Society in Hungary (Hungarian Sociological Studies 3)
No prominent works on this page.
Economy and Society in Hungary (Hungarian Sociological Studies 3)
Confirmation of a theory
Fluvial geomorphologists have tried to describe the outstanding tectonically affected avulsion process of Tisza River at the Great Hungarian Plain by various theoretical concepts.Flume experiments provide the ability to examine the main characteristic processes of a highlighted surface development theory under controlled settings within an accelerated time scale.Our goal was to reconstruct and refine these hypotheses from a new experimental point…
Machine Learning for Gully Feature Extraction Based on a Pan-Sharpened Multispectral Image
Gullies reduce both the quality and quantity of productive land, posing a serious threat to sustainable agriculture, hence, food security. Machine Learning (ML) algorithms are essential tools in the identification of gullies and can assist in strategic decision-making relevant to soil conservation. Nevertheless, accurate identification of gullies is a function of the selected ML algorithms, the image and number of classes used, i.e., binary (two …
Mathematics (2 works) · Soil erosion and sediment transport (2 works) · Alluvial plain (1 works) · Alluvium (1 works) · Artificial Intelligence (1 works) · Binary classification (1 works) · Binary number (1 works) · Coastal plain (1 works) · Computer Science (1 works) · Economics (1 works)