@article {10.3844/jcssp.2022.520.529,
article_type = {journal},
title = {Applications of Artificial Intelligence Based Technologies in Weed and Pest Detection},
author = {Jain, Chakresh Kumar and Gupta, Nidhi and Gupta, Bharat and Passi, Kalpdrum},
volume = {18},
number = {6},
year = {2022},
month = {Jul},
pages = {520-529},
doi = {10.3844/jcssp.2022.520.529},
url = {https://thescipub.com/abstract/jcssp.2022.520.529},
abstract = {Unprecedented population growth and climate change has burdened food security and scarcity worldwide, where the agriculture sector can significantly contribute to accomplishing the demands and contribute to the economic growth of a country. Artificial Intelligence (AI) has revolutionized the agricultural domain. Pest and weed detection is significant to yielding good quality crops. The AI-based tools and technologies such as drones and robots bring advancement in crop production by performing the early detection of weeds and pests. The tools utilize image processing and machine learning algorithms to capture, analyze and detect the presence of weeds and pests in plants. The research work carried out provides a comprehensive survey for the application of artificial intelligence for both weed and pest detection. It presents widely used techniques, their evaluation parameters, and publicly available datasets which provide the current status of work for the researchers working in the domain of weed and pest detection.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}