Optimize Agriculture using Artificial Intelligence

[feedme-foodapp]

[Abstract]

Agriculture plays a significant role in the growth and development of the economy of any nation. But the emergences of crop-related diseases affect the productivity [1]. This has not only an impact on the economy itself, but also influences the security of food supply.

Conventional methods of pest control are mostly controversial and no longer tolerable for the environment. To cope with these issues and to implement effective strategies to prevent the propagation of diseases, crop disease diagnosis with artificial methods is required. Commonly used techniques are k-Means clustering, Convolutional Neural Network CNN, and image processing tasks. In this paper, a combination of Convolutional Neural Network and autoencoder is explained, which is referred as Convolutional Encoder Network, to identify crop disease using crop leaf images.

Keywords

Artificial Intelligence, Machine Learning, Deep Learning, Crop disease detection, Convolutional Encoder Network, PlantVillage

Link to PDF: short_paper_walser.pdf

[Vivinternational]

Optimize Agriculture using Artificial Intelligence_Review.pdf short_paper_walser_review.pdf

[Lav-Mehta]

Review_Optimize Agriculture using Artificial Intelligence_Mehta.pdf

[holzmi-stud-kufstein]

Peer Review Report_02_walser.pdf