Deep learning for tomographic image reconstruction

G Wang, JC Ye, B De Man - Nature machine intelligence, 2020 - nature.com
Deep-learning-based tomographic imaging is an important application of artificial
intelligence and a new frontier of machine learning. Deep learning has been widely used in …

Deep learning on image denoising: An overview

C Tian, L Fei, W Zheng, Y Xu, W Zuo, CW Lin - Neural Networks, 2020 - Elsevier
Deep learning techniques have received much attention in the area of image denoising.
However, there are substantial differences in the various types of deep learning methods …

Deep learning techniques for inverse problems in imaging

G Ongie, A Jalal, CA Metzler… - IEEE Journal on …, 2020 - ieeexplore.ieee.org
Recent work in machine learning shows that deep neural networks can be used to solve a
wide variety of inverse problems arising in computational imaging. We explore the central …

[PDF][PDF] Integrating physics-based modeling with machine learning: A survey

J Willard, X Jia, S Xu, M Steinbach… - arXiv preprint arXiv …, 2020 - beiyulincs.github.io
There is a growing consensus that solutions to complex science and engineering problems
require novel methodologies that are able to integrate traditional physics-based modeling …

Integrating scientific knowledge with machine learning for engineering and environmental systems

J Willard, X Jia, S Xu, M Steinbach, V Kumar - ACM Computing Surveys, 2022 - dl.acm.org
There is a growing consensus that solutions to complex science and engineering problems
require novel methodologies that are able to integrate traditional physics-based modeling …

[HTML][HTML] An overview of deep learning in medical imaging focusing on MRI

AS Lundervold, A Lundervold - Zeitschrift für Medizinische Physik, 2019 - Elsevier
What has happened in machine learning lately, and what does it mean for the future of
medical image analysis? Machine learning has witnessed a tremendous amount of attention …

Diagnosis and detection of infected tissue of COVID-19 patients based on lung X-ray image using convolutional neural network approaches

S Hassantabar, M Ahmadi, A Sharifi - Chaos, Solitons & Fractals, 2020 - Elsevier
COVID-19 pandemic has challenged the world science. The international community tries to
find, apply, or design novel methods for diagnosis and treatment of COVID-19 patients as …

On instabilities of deep learning in image reconstruction and the potential costs of AI

V Antun, F Renna, C Poon, B Adcock… - Proceedings of the …, 2020 - National Acad Sciences
Deep learning, due to its unprecedented success in tasks such as image classification, has
emerged as a new tool in image reconstruction with potential to change the field. In this …

Machine learning for data-driven discovery in solid Earth geoscience

KJ Bergen, PA Johnson, MV de Hoop, GC Beroza - Science, 2019 - science.org
BACKGROUND The solid Earth, oceans, and atmosphere together form a complex
interacting geosystem. Processes relevant to understanding Earth's geosystem behavior …

Applications of artificial intelligence in transport: An overview

R Abduljabbar, H Dia, S Liyanage, SA Bagloee - Sustainability, 2019 - mdpi.com
The rapid pace of developments in Artificial Intelligence (AI) is providing unprecedented
opportunities to enhance the performance of different industries and businesses, including …