Image Generation for Real Time Application Using DCGAN (Deep Convolutional Generative Adversarial Neural Network)

Abstract

As the technology keeps developing the unimaginable possibilities keep happening. And it leads to easy use of our daily life. In image processing when the CNNs came to our life it makes the world to turn around and makes the human work easier in all organization. Convolutional Neural Network were mainly used in computer vision, mainly in face recognition, image classification, action recognition, and document analysis, but these gets difficult when comes to dataset. Gathering dataset for machine learning is time consuming operation, at that point the new technique called GAN were introduced. It can predict that whether the image is real or not, which is a next level improvement of machine learning techniques. Our aim is to improve the creativity of the machine and generate different type of images which will be useful in the fields like animation and designing. Here in our paper, we will use the Deep Convolutional Generative Adversarial Networks (DCGAN) where it will be used to generate new images that are not in the dataset. And it's been a huge success in terms of creating new images. MNIST dataset and Anime dataset   are used here, by using the DCGAN in it and try to create pictures that are similar to the datasets.