On the use of deep learning for computational imaging
Since their inception in the 1930–1960s, the research disciplines of computational imaging
and machine learning have followed parallel tracks and, during the last two decades …
and machine learning have followed parallel tracks and, during the last two decades …
Does deep learning always outperform simple linear regression in optical imaging?
Deep learning has been extensively applied in many optical imaging problems in recent
years. Despite the success, the limitations and drawbacks of deep learning in optical …
years. Despite the success, the limitations and drawbacks of deep learning in optical …
Lensless computational imaging through deep learning
Deep learning has been proven to yield reliably generalizable solutions to numerous
classification and decision tasks. Here, we demonstrate for the first time to our knowledge …
classification and decision tasks. Here, we demonstrate for the first time to our knowledge …
Learning from simulation: An end-to-end deep-learning approach for computational ghost imaging
Artificial intelligence (AI) techniques such as deep learning (DL) for computational imaging
usually require to experimentally collect a large set of labeled data to train a neural network …
usually require to experimentally collect a large set of labeled data to train a neural network …
At the intersection of optics and deep learning: statistical inference, computing, and inverse design
Deep learning has been revolutionizing information processing in many fields of science
and engineering owing to the massively growing amounts of data and the advances in deep …
and engineering owing to the massively growing amounts of data and the advances in deep …
Far-field super-resolution ghost imaging with a deep neural network constraint
F Wang, C Wang, M Chen, W Gong, Y Zhang… - Light: Science & …, 2022 - nature.com
Ghost imaging (GI) facilitates image acquisition under low-light conditions by single-pixel
measurements and thus has great potential in applications in various fields ranging from …
measurements and thus has great potential in applications in various fields ranging from …
Computational imaging
JN Mait, GW Euliss, RA Athale - Advances in Optics and Photonics, 2018 - opg.optica.org
We review advances in Computational Imaging that have occurred since the mid-1990s. The
advent of highly integrated platforms, such as the smartphone, has made the linkage …
advent of highly integrated platforms, such as the smartphone, has made the linkage …
[图书][B] Deep learning in computer vision: principles and applications
M Hassaballah, AI Awad - 2020 - books.google.com
Deep learning algorithms have brought a revolution to the computer vision community by
introducing non-traditional and efficient solutions to several image-related problems that had …
introducing non-traditional and efficient solutions to several image-related problems that had …
Mobile computational photography: A tour
The first mobile camera phone was sold only 20 years ago, when taking pictures with one's
phone was an oddity, and sharing pictures online was unheard of. Today, the smartphone is …
phone was an oddity, and sharing pictures online was unheard of. Today, the smartphone is …
Deep learning-based super-resolution in coherent imaging systems
We present a deep learning framework based on a generative adversarial network (GAN) to
perform super-resolution in coherent imaging systems. We demonstrate that this framework …
perform super-resolution in coherent imaging systems. We demonstrate that this framework …