Data Augmentation Methods to Enhance Performance of CNN for Plant Disease Detection |
Author(s): |
Binzy Nazar , College of Engineering Thalassery, Kannur, Kerala; Shayini R, College of Engineering Thalassery, Kannur, Kerala |
Keywords: |
Deep neural networks, CNN, Data augmentation, Plant disease detection |
Abstract |
Image data augmentation is a technique that can be used to artificially expand the size of a training dataset by creating modified versions of images in the dataset. Training deep learning neural network models on more data can result in more skillful models, and the augmentation techniques can create variations of the images that can improve the ability of the fit models to generalize what they have learned to new images To increase performance of CNN we can use various types of augmentation methods. In this paper we are discussing about the techniques used to increase the data set size for plant disease detection. Here we take Chili plant diseases as an example and try to increase the collected real time data set size using various augmentation methods. |
Other Details |
Paper ID: IJSRDV9I10061 Published in: Volume : 9, Issue : 1 Publication Date: 01/04/2021 Page(s): 95-97 |
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