Automation in Agriculture by Machine and Deep Learning Techniques: A Review of Recent Developments

• Published in: Precision agriculture Vol. 22; no. 6; pp. 2053 - 2091
• Main Authors: Saleem, Muhammad Hammad, Potgieter, Johan, Arif, Khalid Mahmood
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.12.2021; Springer Nature B.V
• Subjects: Agricultural equipment; Agricultural land; Agriculture; Algorithms; Artificial intelligence; Artificial neural networks; Atmospheric Sciences; Automation; Biomedical and Life Sciences; Chemistry and Earth Sciences; Classification; Computer Science; Crop diseases; Crops; Deep learning; Discrimination; Disease detection; Feature extraction; fruits; Land cover; Learning algorithms; Life Sciences; Machine learning; Multilayers; Neural networks; Physics; Plant diseases; precision agriculture; Remote Sensing/Photogrammetry; Review; robots; Soil Science & Conservation; Statistics for Engineering; Support vector machines; weeds; Deep learning; Fruit harvesting; Plant disease detection; Agricultural robotics; Convolutional neural network; Machine learning

Recently, agriculture has gained much attention regarding automation by artificial intelligence techniques and robotic systems. Particularly, with the advancements in machine learning (ML) concepts, significant improvements have been observed in agricultural tasks. The ability of automatic feature e...