학술논문

Crop Disease Prediction using Machine Learning and Deep Learning: An Exploratory Study
Document Type
Conference
Source
2023 International Conference on Sustainable Computing and Smart Systems (ICSCSS) Sustainable Computing and Smart Systems (ICSCSS), 2023 International Conference on. :278-283 Jun, 2023
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Deep learning
Pathogens
Insects
Crops
Diseases
Farming
Business
Crop disease
Agriculture
Machine learning
Language
Abstract
Crop diseases are caused by pests, insects, and pathogens, and if not promptly handled, they significantly reduce the yield. Farmers are losing money because of different crop diseases. When the cultivated area is large (in acres), it becomes tiresome for the cultivators to examine the crops regularly. The farming business needs an automatic crop disease identification and analysis. It may be used to diminish the loss of money and other resources, reduce yield losses, and enhance the effectiveness of treatment leading to healthier crop output. Many industries today have benefited from the development of new technologies, particularly artificial intelligence, Machine Learning (ML) and Deep Learning (DL). This study examined the significant advancements and issues, such as reduction in harvest yield, lower quality of produce and crop damage, using ML and DL approaches for crop disease detection and prediction in the recent studies.