mulliGAN

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In Folder: mulliGAN A diverse GAN experimentation platform

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mulliGAN

Senior Design Showcase project, Wentworth Institute of Technology, College of Engineering and Computer Science, Department of Computer Science and Networking, 2020

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title: mulliGAN

creator: Paul Medeiros, Shawn Shao

subject: Generative Adversarial Network (GAN), Machine learning, Web application

description: The world of machine learning in both consumer technologies and the research sector is rapidly growing and strives to find and use large quantities of useful data to produce strong user applications. With emerging machine learning technologies, such as Generative Adversarial Networks (GANs), researchers and software engineers alike have been focusing on the technology’s capabilities of generative models and their ability to generate realistic examples across a range of problem domains. The goal of the project is to construct a GAN that is capable of extracting images from Google Images and using them as training and testing data for the GAN. We propose to have a web service for the users to interact with the GAN and specify the type of images that should be generated, such as cat, dog, …, etc. The web service not only has a backend API that controls the search parameters for the GAN algorithm, but it also collects and organizes the data for users to view or download the resulting images. The service could also potentially be used to produce copyright-free images for use in experimental testing data. We believe our service can provide a wide variety of sample images for the researchers and software engineers to advance their work in the machine learning field.

publisher: The Douglas D. Schumann Library and Learning Commons, Wentworth Institute of Technology

contributor:

date: 2020

type: Poster

format: .pdf

identifier:

source:

language: eng

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coverage:

rights: https://rightsstatements.org/vocab/InC/1.0/

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