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Title

Analysis of Recognition Performance of Plant Leaf Diseases Based on Machine Vision Techniques

Author

Imdadul Haque, Mahbub Alam, Md. Tarek Habib, Mohsin Alim, Samia Nawshin, Sheak Rashed Haider Noori,

Email

Abstract

Agriculture is the primary source of income for the majority of the population in Bangladesh. Agriculture is also a big

part of the economy of the country. Therefore, it's more necessary to grow our crops and fruits and boost their harvests.

Fruits are adored by the people of this country, and farmers love growing fruits. Owing to numerous diseases, both the

quality and quantity of fruits are not meeting expectations. Native fruits are contracting many types of new diseases, and

the magnitude of the problem is increasing alarmingly. To deal with this issue, quick detection of the disease and correct

treatment or recuperation is required. In many cases, locals fail to even detect rare diseases. Thanks to the hug

e

advancement in technology, rare diseases can now be detected with the use of the right technologies. A good plant's

growth is dependent on its leaves. Early leaf disease detection can help in keeping the leaves disease-free, as well as the

plants and fruits. Our research focuses on identifying litchi leaf diseases by employing sophisticated image processing

technologies to ensure the freshness of the leaves. A machine-vision-based technique, i.e., the

Convolutional Neural

Network

(CNN), has been used in this research work.

Keywords

Agriculture; Litchi; Leaf Disease; Deep Learning; Convolutional Neural Network; Plants ; Disease Recognition

Journal or Conference Name

Journal of Human, Earth, and Future

Publication Year

2022

Indexing

scopus