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Crafting Images With Generative Adversarial Networks (GANs) and Models
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The chapter “Challenges and Future Directions” in the book “Crafting Images with Generative Adversarial Networks (GANs) and Models” delves into the current obstacles and prospective advancements in the realm of GANs and generative models. This chapter aims to provide readers with a thorough understanding of the primary issues hindering the progress and broader application of GANs, while also highlighting the innovative solutions and future directions that could address these challenges. The first section of the chapter explores the major challenges faced by researchers and practitioners in the field of GANs. These include training instability, where GANs often suffer from issues like mode collapse and vanishing gradients, making the training process unpredictable and inefficient.
Title: Crafting Images With Generative Adversarial Networks (GANs) and Models
Description:
The chapter “Challenges and Future Directions” in the book “Crafting Images with Generative Adversarial Networks (GANs) and Models” delves into the current obstacles and prospective advancements in the realm of GANs and generative models.
This chapter aims to provide readers with a thorough understanding of the primary issues hindering the progress and broader application of GANs, while also highlighting the innovative solutions and future directions that could address these challenges.
The first section of the chapter explores the major challenges faced by researchers and practitioners in the field of GANs.
These include training instability, where GANs often suffer from issues like mode collapse and vanishing gradients, making the training process unpredictable and inefficient.
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