Deep Learning in Mass Spectrometry Imaging
Lead Research Organisation:
University of Surrey
Department Name: Computing Science
Abstract
The research project aims to develop new and innovative machine learning algorithms to analyse the data from the new 3D OrbiSIMS instrument in a time and memory efficient manner. The work will concentrate upon machine learning, data-mining, statistical and pattern recognition techniques.
People |
ORCID iD |
Yaochu Jin (Primary Supervisor) | |
Foivos Ntelemis (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/R512126/1 | 01/10/2017 | 30/09/2022 | |||
2075545 | Studentship | EP/R512126/1 | 02/07/2018 | 30/06/2022 | Foivos Ntelemis |
Title | Information Maximization Clustering via Representation Learning Technique |
Description | This newly developed algorithm, based on deep learning, extends a representation learning technique by operating simultaneously to provide effective clustering performance and dimensionality reduction (representation learning). Additionally, the computational time of the algorithm has been improved. This work has been submitted to a conference and is under review. |
Type Of Material | Computer model/algorithm |
Year Produced | 2021 |
Provided To Others? | No |
Impact | This new algorithm presents a single-phase framework for data clustering and reduction. By training in a single phase, it provides an advantage in term of computation cost. The algorithm has shown strong robustness and effectiveness in various types of data. |
Title | Visual Clustering via Generative Adversarial Networks and Information Maximisation |
Description | The subject algorithm is an innovative deep learning technique which is developed during the past period for grouping visual and high dimensional data into a given number of categories based on their similarities. The algorithm has been evaluated successfully in Mass Spectrometry data. At current stage, this method is under review for publication. |
Type Of Material | Computer model/algorithm |
Year Produced | 2020 |
Provided To Others? | No |
Impact | This new algorithm provides the facility for quick clustering high dimensional datasets including visual or spectra data. Currently, the algorithm has been used to remove the background in Mass Spectrometry Imaging. |