Generating Synthetic Dataset for Cotton Leaf using DCGAN

In recent times deep learning and machine learning algorithms has a major role in the advancement of emerging technologies and also in various sectors like: Agricultural, educational, industrial etc. But a major drawbackwith ML and DL algorithms is to find a suitable and apt datasetwith huge number of samples to train a model. So, in this paperwork we have implemented data augmentation for cotton leaves by generating a synthetic dataset using DCGAN (Deep Convolutional Generative Adversarial Network). Syntheticdataset is an artificial dataset which uses various artificial algorithms to generates a new dataset with larger number of samples. Hence in this work we have used DCGAN algorithm to generate a synthetic dataset, which effectively generates a new dataset for cotton leaves with images similar to the original dataset.