No abstract

No abstract

No abstract

No abstract

Plant diseases is one of the major bottlenecks in agricultural production that have bad eects on the economic of any country. Automatic detection of such disease could minimize these eects. Features selection is a usual pre-processing step used for automatic disease detection systems. It is an important process for detecting and eliminating noisy, irrelevant, and redundant data. Thus, it could lead to improve the detection performance. In this paper, an improved moth-ame approach to automatically detect tomato diseases was proposed.

No abstract

No abstract

No abstract