By ucla ita Diffractive deep neural networks (D2NNs) are optical systems composed of successive transmissive layers optimized through deep learning to perform computational tasks in an all-optical manner.
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By ucla ita The team from UCLA has introduced an information-hiding camera that integrates an optical encoder with an electronic decoder, jointly optimized through deep learning.
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By ucla ita Scientists at UCLA have unveiled a groundbreaking technology that could revolutionize the fields of imaging and optical communications.
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By ucla ita Traditional optical imaging technologies rely on intensity-based sensors that can only capture the amplitude of light, leaving out the crucial phase information.
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By ucla ita While image denoising algorithms have undergone extensive research and advancements in the past decades, classical denoising techniques often necessitate numerous iterations for their inference, making them less suitable for real-time applications.
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By UCLA ITA Polarization describes the orientation of oscillations in a light wave, and it plays an essential role in various optical applications — from enhancing visibility in sunglasses and camera lenses to facilitating advanced optical communication and...
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By UCLA ITA Information processing with light is a topic of ever-increasing interest among optics and photonics researchers.
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By UCLA ITA For decades, imaging weakly scattering phase objects, such as cells, has been an active area of research across various fields, including biomedical sciences.
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By UCLA ITA Multispectral imaging has fueled major advances in various fields, including environmental monitoring, astronomy, agricultural sciences, biomedicine, medical diagnostics and food quality control.
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