Face Generation Model Based on DCGAN
Keywords:
Convolutional Neural Network, Generative Adversarial Network, Deep Convolutional Generative Adversarial Network, Face GenerationAbstract
After breakthroughs in computer hardware technology, deep learning has undoubtedly become the biggest winner in the field of learning. Various deep neural networks have achieved remarkable progress in computer vision, speech processing, and natural language processing. By combining CNN with the traditional GAN, DCGAN has made significant advances in unsupervised learning. In this paper, we train the original DCGAN using Python on the TensorFlow deep-learning framework and apply commonly used network-optimization techniques in deep learning, ultimately generating face images that share the same characteristics as the training samples.
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Copyright (c) 2025 Yu Dong, Zhou Li
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
