TY  - JOUR
AU  - Jain, Chakresh Kumar 
AU  - Gupta, Nidhi 
AU  - Gupta, Bharat 
AU  - Passi, Kalpdrum 
PY  - 2022
TI  - Applications of Artificial Intelligence Based Technologies in Weed and Pest Detection
JF  - Journal of Computer Science
VL  - 18
IS  - 6
DO  - 10.3844/jcssp.2022.520.529
UR  - https://thescipub.com/abstract/jcssp.2022.520.529
AB  - 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.