The London Imaging Meeting (LIM 2021) promotes synergies between imaging science and deep learning.

We are interested in two aspects of deep-learning and imaging science research, case studies, or work-in-progress that lead and seed future research directions:
*Imaging science to improve deep learning performance
*Deep learning methods intended to improve imaging systems performance

PROGRAM TOPICS include but are not limited to
. The impact of imaging system design and optimization on DNN performance

. Imaging system modeling for data augmentation for DNN training

. Metrification of imaging performance for DNN input

. DNNs for metrification of imaging systems; optimization of imaging performance; and image quality prediction

. DNN components and domain adaptations for imaging systems

SUBMISSION DEADLINES
*Journal-first Deadline: 5 April
*Conference Proceedings Deadline: 30 April

CALL FOR PAPERS http://bit.ly/LIM_2021_CallforPapers

KEYWORDS: imaging science, imaging systems, imaging performance, deep learning, DNN, deep neural networks, AI, artificial intelligence

Connect with us on LinkedIn and @ImagingOrg #LondonImaging

Roberta Morehouse, CMP
Communications and Marketing Manager
Society for Imaging Science and Technology (IS&T)
-imaging across applications-imaging.org
IS&T is a non-profit organization dedicated to advancing science and technology in the field of imaging.