International Journal For Multidisciplinary Research

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Deep Learning for Green Growth: Custom CNN Uncovers Cucumber Leaf Disease Secrets

Author(s) Mohammad Tahmid Noor, B. M. Shahria Alam, Golam Kibria, Sidratul Moontaha, Fahad Ahammed
Country Bangladesh
Abstract There are many popular vegetables in the world, among them cucumber is one of the most famous and healthiest foods. It comes with multiple health benefits, especially in losing weight and in skincare. However, there can be multiple diseases that can attack the cucumber leaf and the cucumber itself. Cucumber leaf disease research plays a cardinal role in agricultural fields. Cucumber leaf disease is a special disease that harms its leaves and causes different types of diseases. In real fields, it is difficult to identify different diseases on the leaf due to the complex environment. It is also a very challenging and time-consuming process to identify leaf diseases. To overcome those barriers and detect the diseases we have used two learning methods namely DenseNet201 and VGG16 model. In this research, we have created a new dataset with four classes containing 2159 pictures with an accuracy rate of 98.97% from DenseNet201. The image recognition methods choose the image and find the disease's spot by breaking the image frame by frame. We have rescaled all the images while preprocessing where the image size is 224×224. The methods show great success in finding the disease spots.
Keywords CNN, Cucumber, Disease, Machine learning, Image Classification
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 6, Issue 6, November-December 2024
Published On 2024-12-07
Cite This Deep Learning for Green Growth: Custom CNN Uncovers Cucumber Leaf Disease Secrets - Mohammad Tahmid Noor, B. M. Shahria Alam, Golam Kibria, Sidratul Moontaha, Fahad Ahammed - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.32327
DOI https://doi.org/10.36948/ijfmr.2024.v06i06.32327
Short DOI https://doi.org/g8t3kb
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