Machine Learning and Spectral Analysis for Smart Sensing
Deadline for manuscript submissions: closed (20 August 2021) | Viewed by 2097
Interests: machine learning; chemometrics; spectroscopy; sensors; food authentication; virus detection
Special Issues, Collections and Topics in MDPI journals
Interests: plasma emission spectroscopy; IR spectroscopy; trace gas sensing; aerosol sensing; autonomous environmental sensors; ocean sensing
Interests: chemometrics; sensing; machine learning
Recent advances in artificial intelligence, machine and deep learning and signal processing have the potential to transform the field of spectral data analysis with significant impact in sensing applications such as food authentication, virus detection and quality monitoring. Spectral data analysis is fast and often accurate, so it has allowed developments of sensing technologies that have broadened the range of applications, lowered deployment costs, improved performance and resolution, and increased portability and miniaturization for applications beyond the laboratory. These technologies enable the provision of solutions to many real-world challenges where non-destructive, in situ, fast-processing and cost-effective analyses are sought.
This Special Issue puts a particular emphasis on machine and deep learning and signal processing in its broadest sense applied to spectral data analysis for sensing applications including food authentication, virus detection and quality monitoring. This issue will cover, but is not limited to, the following topics:
- Signal processing, normalization, calibration and filtering;
- Machine and deep learning and modelling;
- Data-driven models and source separation;
- Pattern recognition and classification;
- Image processing and hyperspectral and multispectral imaging applications;
- UV–Vis–NIR spectroscopy;
- Surface-enhanced Raman scattering (SERS) spectroscopy;
- Bio-inspired sensors and systems;
- Portable and miniature spectrometers.
Prof. Dr. Hui Wang
Prof. Dr. Paul Maguire
Dr. Omar Nibouche
Dr. Weiran Song
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Chemosensors is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- Machine learning
- Deep learning
- Signal processing
- Spectroscopy and chemometrics
- Smart sensors
- Food authentication and quality monitoring, virus detection, and other applications