Aydogan discusses the unique advantages of holography in capturing both amplitude and phase information without the need for physical focusing mechanisms. He explains how neural networks can be trained to not only reconstruct holographic images but also to autofocus on multiple objects within a sample, enhancing the depth of field. The conversation delves into the architecture of these networks, highlighting their ability to learn complex transformations while maintaining a connection to the underlying physics.
