Feature Issue of Applied Optics
Artificial Intelligence and Machine Learning in Optical Information Processing
Submission Opens: 1 August 2021
Submission Deadline: 1 October 2021
The recent advances in Artificial Intelligence (AI) and Machine Learning (ML) methods have enabled new utility of existing optical sensing, imaging and processing technology, allowing for a proliferation of its use in practical life. A significant portion of the new application areas involve optics and imaging.
This feature issue of Applied Optics aims to broadly span the current state-of-the-art in application of AI/ML in areas such as: opto-mechanical design and build, computational imaging, image restoration, image recognition, signal classification, machine inspection/vision and explainable AI as it pertains to optical sensing and optics/imaging. Other uses of ML used in Optical imaging for medical applications, diagnostics and pathogen detection are of high interest because of the COVID pandemic.
We welcome manuscripts directed at specific applications, or more broad survey papers that capture the current state of application in areas such as health care, robotics, automotive, climate, high energy physics, remote sensing, etc.
Topics of interest include, but are not limited to, the following:
- AI/ML used for image recognition or signal classification
- AI/ML used for optical component design
- Explainable AI applied to Optical Information Processing
- Analysis and comparison of methods applied to problems of interest
- AI/ML used for diagnostic using optical imaging (other modes of imaging may be accepted based on editor's discretion)
- Pathogens detection using optical imaging, smart phone, etc.
- AI/ML used in High Power Laser operation, alignment, uncertainty quantification, optics inspection, parameter selection and experimental design
- AI/ML in Optical Communications
- AI/ML in Optical signal and image Processing
- AI/ML in Image compression, optical sensing, compressive sensing
- AI/ML in Computational Imaging
- AI/ML for high throughput real-time optical microscopy
- AI/ML for super resolution microscopy
- AI/ML for multi-modal microscopy
- Ethics and diversity issues in AI, face recognition and security applications
All submissions need to present original, previously unpublished work and will be subject to the normal standards and peer review processes of the journal. The standard Applied Optics Publication Charges will apply to all published articles.
Please prepare manuscripts according to the author instructions for submission to Applied Optics and submit through Prism's manuscript submission system, specifying from the drop-down menu that the manuscript is for the Feature Issue on Artificial Intelligence and Machine Learning in Optical Information Processing.
Feature Editors
Khan Iftekharuddin, Old Dominion University, USA (Lead Editor)
Abdul Ahad S. Awwal, Lawrence Livermore National Laboratory, USA
Chrysanthe Preza, The University of Memphis, USA
Michael E. Zelinski, Lawrence Livermore National Laboratory, USA