| Autor: |
Bali, Nishu, Singla, Anshu, Chaudhary, Deepika, Nagpal, Pallavi |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2023, Vol. 2916 Issue 1, p1-7, 7p |
| Abstrakt: |
Agriculture is one of the most important fields of study as it helps in ensuring food for masses. The study involves various important parameters related to climate and soil. Among these, soil is one of the most important parameter as it acts as the base for fulfilling water and nutrient requirements of the plant. The study of soil characteristics has always been a challenge for the researchers as it exhibits large nonlinear variations both spatially and temporally. The advancements in the field of machine learning and deep learning has provided solutions in the form of diverse algorithms for studying the chemical and physical properties of the soil. The present study provides an extensive review of various machine learning and deep learning models used for studying the physical and chemical characteristics of soils of various regions. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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