解开谜团基于 DCGAN 的草图到真实人脸的转换

Nishiket Waghmode, Pravin Bansode, Digambar Chalkapure, Ms. Uttara Varade
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引用次数: 0

摘要

本文探讨了人工智能(AI)在通过人脸识别识别罪犯方面的高级应用,特别是利用深度卷积生成对抗网络(DCGAN)将法医草图转化为逼真的照片。当证人对罪犯进行描述时,专家会根据描述绘制法医草图。通过使用 DCGAN,该素描被输入到神经网络中,经过训练后,神经网络就能生成准确、逼真的嫌疑人面部图像。这项技术可以根据基本素描,甚至是不完整的素描或各种姿势的素描,快速生成详细的高分辨率图像,从而极大地帮助犯罪调查。这种方法在法医、执法、面部识别和安全系统中非常有价值,可提高犯罪识别的效率和准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Solve the Mystery: DCGAN-Based Sketch to Real Face Conversion
This paper explores the advanced application of Artificial Intelligence (AI) in criminal identification through facial recognition, specifically by transforming forensic sketches into realistic photos using Deep Convolutional Generative Adversarial Networks (DCGAN). When a witness provides a description of a criminal, an expert creates a forensic sketch based on this description. By using DCGAN, this sketch is fed to into a neural network, which, after training, generates accurate, realistic facial images of the suspect. This technique significantly aids crime investigations by quickly producing detailed, high-resolution images from basic sketches, even those that are incomplete or depict various poses. The method is valuable in forensics, law enforcement, facial recognition, and security systems, enhancing the efficiency and accuracy of criminal identification
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