International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 09 Issue: 05 | May 2022
p-ISSN: 2395-0072
www.irjet.net
Convolutional Neural Network for Leaf and citrus fruit disease identification using deep learning model Ragavi .R1, Kaviya Sri .S2, Pooja Rao .P3, Ms. Thenmozhi .R AP (Sel.G)4 1,2,3 SRM
Valliammai Engineering College, Kattankulathur, Chennai 4 Associate Professor, Department of Information Technology, SRM Valliammai Engineering College, Tamil Nadu, India ---------------------------------------------------------------------***--------------------------------------------------------------------Southeast Asia. The most widely recognized are oranges, Abstract - Grouping of the different sorts of citrus organic
grapefruits, tangerines, lemons, and limes. Citrus organic products contain many mixtures that can assist with keeping your heart sound. Their dissolvable fiber and flavonoids may assist with raising solid HDL cholesterol and lower unsafe LDL cholesterol and fatty substances. The natural products might bring down hypertension, another gamble factor for coronary illness.
products in light of their skin tone is an arduous errand and consumes a ton of time. An automated framework whenever prepared to arrange citrus organic products in light of their external skin tone, it would be of extraordinary assistance for the ventures that perform arranging and evaluating of the farming items.
The target giving a viewpoint to the arrangement of seven various types of citrus leafy foods by a prepared computerized framework. The framework is prepared to such an extent that it would anticipate the biggest maker of the concerned citrus organic product on the planet and will likewise pass on a message containing the supplement worth or medical advantages of the particular citrus organic product.
Convolutional brain networks are profound learning calculations that are exceptionally strong for the picture handling is utilized to examination the leaf and natural product qualities. The rural area is a huge and new system for scientists in the field of PC vision today. Agribusiness' essential objective is to create a wide scope of important and significant harvests and plants. In cultivating, plant microorganisms lessen the sum and attributes of the item, so they should be controlled early.
The pre-prepared convolution brain network models like AlexNet and LeNet Architecture when retrained with a dataset of 2029 pictures gave us attainable outcomes. The exploratory outcomes as exactness and misfortune rate displayed in the charts approves the adequacy of the proposed methods.
As of late, rural analysts have zeroed in their endeavors on infections of different foods grown from the ground. The analysts concocted a few strategies for distinguishing and grouping infections in foods grown from the ground . Pre-handling and side effect division are finished utilizing an assortment of new strategies.
Keywords : Citrus Fruits & Leaves Classification, Neural Network, Tensorflow
II. LITERATURE SURVEY
I. INTRODUCTION
[1] The proposed CNN model extracts complementary discriminative features by integrating multiple layers. The CNN model was checked against many state-of-the-art deep learning models on the Citrus and Plant Village datasets. According to the experimental results, the CNN Model outperforms the competitors in a variety of measurement metrics. The CNN Model has a test accuracy of 94.55 percent, making it a valuable decision support tool for farmers looking to classify citrus fruit/leaf diseases.
Farming examination means to increment food creation and quality while bringing down costs and helping benefits. Natural product trees assume a significant part in any state's monetary turn of events. One of the most notable natural product plant species is the citrus plant, which is high in L-ascorbic acid. Citrus organic products are known as agrumes, which generally signifies "harsh organic products". Most citrus natural products are from a little gathering of plants that are presumably gotten from around four species in
© 2022, IRJET
|
Impact Factor value: 7.529
|
ISO 9001:2008 Certified Journal
|
Page 390