Investigating the effect of loss functions on single-image GAN performance
Loss functions are crucial in training generative adversarial networks (GANs) and shaping the resulting outputs. These functions, specifically designed for GANs, optimize generator and discriminator networks together but in opposite directions. GAN models, which typically handle large datasets, have...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Bursa Technical University
2024-12-01
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| Series: | Journal of Innovative Science and Engineering |
| Subjects: | |
| Online Access: | http://jise.btu.edu.tr/en/download/article-file/3991473 |
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