| Abstrakt: |
Deep learning, a subfield of artificial intelligence, has gained significant role in various domains, including agriculture. With the growing need to improve agricultural practices, enhance productivity, and face challenges such as crop yield prediction, disease detection, weed management, irrigation optimization, and livestock monitoring, deep learning has emerged as a valuable tool. The application of deep learning in agriculture, highlighting its potential to modernize farming practices. Overall, deep learning in agriculture holds immense promise, empowering farmers with data-driven insights, sustainability, and efficient resource utilization, increased productivity and profitability while minimizing environmental impact. [ABSTRACT FROM AUTHOR] |
