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Image Synthesis Using Machine Learning Techniques

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Intelligent Data Communication Technologies and Internet of Things (ICICI 2019)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 38))

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Abstract

Image synthesis is the generation of realistic images using a computer algorithm. This can be difficult and time-consuming. Image synthesis using machine learning aims to make this process easier and more accessible. The most prominent machine learning model for generating content is known as generative adversarial networks. This paper reviews and evaluates various generative model based on GANs. These various models are evaluated using inception score and Fréchet inception distance. These are common metrics for the evaluation of generative adversarial networks.

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Author information

Authors and Affiliations

  1. Amity School of Engineering and Technology, Amity University Uttar Pradesh, Noida, UP, India

    Param Gupta & Shipra Shukla

Authors
  1. Param Gupta
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  2. Shipra Shukla
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Corresponding author

Correspondence to Shipra Shukla .

Editor information

Editors and Affiliations

  1. Department of ECE, Karunya University, Coimbatore, India

    D. Jude Hemanth

  2. Department of Electronics and Computer Engineering, Tribhuvan University, Kirtipur, Nepal

    Subarna Shakya

  3. School of Science, Edith Cowan University, Joondalup Campus, Joondalup, WA, Australia

    Zubair Baig

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Gupta, P., Shukla, S. (2020). Image Synthesis Using Machine Learning Techniques. In: Hemanth, D., Shakya, S., Baig, Z. (eds) Intelligent Data Communication Technologies and Internet of Things. ICICI 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 38. Springer, Cham. https://doi.org/10.1007/978-3-030-34080-3_35

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