Face Sketch to Image Generation using Hybrid  GAN

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Pranav Asane; Shantanu Kharade; Shubham Tapale; Neeraj Kalambe; Priti Malkhede

Face Sketch to Image Generation using Hybrid GAN

Authors: Pranav Asane, Shantanu Kharade, Shubham Tapale, Neeraj Kalambe, Priti Malkhede

Unique Paper ID: 171761
Volume: 11
Issue: 8
PageNo: 1357-1361

Keywords: Sketch-to-image generation Generative Adversarial Networks Hybrid GANs Image synthesis Web- based tools.

Abstract:
Creating lifelike facial images from hand-drawn sketches is a complex task with broad applications, ranging from artistic and design purposes to criminal investigations. This paper presents an innovative web application powered by a hybrid Generative Adversarial Network (GAN) model, combining the strengths of DCGAN and Cycle-GAN for superior image synthesis. Users can seamlessly upload sketches, generate high-quality images, and download results, supported by real-time processing feedback. The architecture, featuring an intuitive interface and advanced GAN training methods, is discussed alongside evaluation metrics for image fidelity. This approach opens new avenues for digital creativity and practical use in law enforcement.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 8
PageNo: 1357-1361

Face Sketch to Image Generation using Hybrid GAN

Available:https://ijirt.org/article?manuscript=171761

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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