Prediction of Soil Organic Matter with Deep Learning
Yazarlar (5)
Türkiye
Doç. Dr. Özkan İNİK
Tokat Gaziosmanpaşa Üniversitesi, Türkiye
Türkiye
Türkiye
Türkiye
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale |
| Dergi Adı | ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING |
| Dergi ISSN | 2193-567X Wos Dergi Scopus Dergi |
| Dergi Tarandığı Indeksler | SCI-Expanded |
| Dergi Grubu | Q2 |
| Makale Dili | İngilizce |
| Basım Tarihi | 08-2023 |
| Cilt No | 48 |
| Sayı | 8 |
| Sayfalar | 10227 / 10247 |
| DOI Numarası | 10.1007/s13369-022-07575-x |
| Makale Linki | http://dx.doi.org/10.1007/s13369-022-07575-x |
| Özet |
| Soil is the most important component of the ecosystem and the most significant characteristic of soil is its organic matter content, because organic matter undertakes many tasks by preventing soil moisture, absorption of water after rainfall, and good aeration by correcting bad textural properties and preventing soil erosion. Therefore, its recognition is critical, but the biggest problem is that determining soil organic matter with traditional methods is very laborious, expensive, and time-consuming. Accordingly, as in many different areas, computer vision methods can be used to determine soil organic matter. In this study, a new method based on deep learning has been proposed for the estimation of soil organic matter. In the study, firstly, images of 20 points where soil organic matter content was determined were taken with a special system. Then, a new segmentation method was applied to these images to separate the … |
| Anahtar Kelimeler |
| Soil organic matter | SOM prediction | Deep learning | Convolutional neural networks |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| WoS | 6 |
| Google Scholar | 12 |