Cassava Plant Leaf Disease Detection
Abstract: There are various machine learning algorithms being implemented across the agricultural domain as well as other computer vision domains for the image classification problems as well as object detection problems. These algorithms work on feature extraction from the images. One of the most used algorithms is Convolutional Neural Network (CNN), which helps in feature extraction. Another method which is currently ruling the realm of machine learning is transfer learning, where the knowledge gained by machine while learning to solve one problem is applied for solving another problem. This paper demonstrates how various CNN architectures and transfer learning techniques can be applied for the disease detection in cassava plant.
Keywords: Image Classification, Cassava, Agriculture, Convolutional neural networks, transfer learning
How to Cite?: Yogeshwar Shendye, "Cassava Plant Leaf Disease Detection", Volume 10 Issue 7, July 2021, International Journal of Science and Research (IJSR), Pages: 907-910, https://www.ijsr.net/getabstract.php?paperid=SR21716223603, DOI: https://dx.doi.org/10.21275/SR21716223603